From 36707c474b67e6d0d8fd9db770f2080fe978e3e7 Mon Sep 17 00:00:00 2001 From: Angelo Ziletti Date: Tue, 30 Jan 2018 14:36:15 +0100 Subject: [PATCH] Fix bug in handling non-periodic structures. --- .../custom-analytics-example-dev.bkr | 3422 +++++++++++++++-- 1 file changed, 3187 insertions(+), 235 deletions(-) diff --git a/custom-analytics-example/custom-analytics-example-dev.bkr b/custom-analytics-example/custom-analytics-example-dev.bkr index 955c57a..f7b32e4 100644 --- a/custom-analytics-example/custom-analytics-example-dev.bkr +++ b/custom-analytics-example/custom-analytics-example-dev.bkr @@ -100,7 +100,7 @@ " ", " 1 Fritz Haber Institute of the Max Planck Society, Faradayweg 4-6, D-14195 Berlin, Germany
", " 2 Engineering Laboratory, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK", - " [Last updated: January 30, 2018]", + " [Last updated: January 30, 2018]", "

", "" ], @@ -111,7 +111,7 @@ "result": { "type": "BeakerDisplay", "innertype": "Html", - "object": "\n
\n

NOMAD Analytics Toolkit

\n

On-the-fly data analysis for the NOMAD Archive

\n

\n created by:\n Angelo Ziletti 1,\n Carl Poelking2, \n Fawzi Mohamed1, \n Gábor Csányi2, \n and Luca Ghiringhelli1

\n \n 1 Fritz Haber Institute of the Max Planck Society, Faradayweg 4-6, D-14195 Berlin, Germany
\n 2 Engineering Laboratory, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK\n [Last updated: January 30, 2018]\n

\n
" + "object": "\n
\n

NOMAD Analytics Toolkit

\n

On-the-fly data analysis for the NOMAD Archive

\n

\n created by:\n Angelo Ziletti 1,\n Carl Poelking2, \n Fawzi Mohamed1, \n Gábor Csányi2, \n and Luca Ghiringhelli1

\n \n 1 Fritz Haber Institute of the Max Planck Society, Faradayweg 4-6, D-14195 Berlin, Germany
\n 2 Engineering Laboratory, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK\n [Last updated: January 30, 2018]\n

\n
" }, "selectedType": "BeakerDisplay", "elapsedTime": 0, @@ -317,7 +317,7 @@ "import tempfile", "import ase", "from pymatgen.io.ase import AseAtomsAdaptor", - "from pymatgen.symmetry.analyzer import SpacegroupAnalyzer", + "from pymatgen.symmetry.analyzer import SpacegroupAnalyzer, PointGroupAnalyzer", "", "import soap", "import soap.soapy.util", @@ -326,10 +326,11 @@ "from soap.soapy.momo import osio, endl, flush", "from soap.tools import AseConfig", "", - "from nomad_sim.nomad_structures import NOMADStructure", + "#from nomad_sim.nomad_structures import NOMADStructure", "from nomad_sim.wrappers import get_json_list", "from nomad_sim.wrappers import plot, logger", - "from nomad_sim.wrappers import _get_structures", + "#from nomad_sim.wrappers import _get_structures", + "from nomad_sim.wrappers import _apply_operations", "from nomad_sim.utils_crystals import get_spacegroup", "from nomad_sim.utils_crystals import create_supercell", "from nomad_sim.utils_crystals import filter_json_list", @@ -341,28 +342,15 @@ }, "output": { "state": {}, - "selectedType": "Results", + "selectedType": "Hidden", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 3893, - "height": 50, - "hidden": true, - "result": { - "type": "Results", - "outputdata": [ - { - "type": "err", - "value": "/usr/local/lib/python2.7/dist-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n from ._conv import register_converters as _register_converters\n/usr/local/lib/python2.7/dist-packages/pymatgen/__init__.py:87: UserWarning: \nPymatgen will drop Py2k support from v2019.1.1. Pls consult the documentation\nat https://www.pymatgen.org for more details.\n at https://www.pymatgen.org for more details.\"\"\")\n" - }, - { - "type": "err", - "value": "Using TensorFlow backend.\n" - } - ] - } + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 338, + "height": 51, + "hidden": true }, "evaluatorReader": true, - "lineCount": 38, + "lineCount": 39, "initialization": true, "tags": "query_list" }, @@ -2443,8 +2431,8 @@ }, "selectedType": "Table", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 1000, + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 258, "dataresult": 1, "height": 785 }, @@ -2814,7 +2802,7 @@ "result": { "type": "BeakerDisplay", "innertype": "Html", - "object": "\n\n\n\n

Control options Query

\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Name of query to analyze (if empty: load latest query)\n \n\n
Max number or results for each space group/point group \n \n
\n \n

\n\n

Control options Analysis

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Atomic density \n \n \n \n \n
Basis set \n \n \n \n
Base kernel \n \n \n \n
Top kernel \n \n \n \n
\n \n
\n \n \n \n \n" + "object": "\n\n\n\n

Control options Query

\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Name of query to analyze (if empty: load latest query)\n \n\n
Max number or results for each space group/point group \n \n
\n \n

\n\n

Control options Analysis

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Atomic density \n \n \n \n \n
Basis set \n \n \n \n
Base kernel \n \n \n \n
Top kernel \n \n \n \n
\n \n
\n \n \n \n \n" }, "selectedType": "BeakerDisplay", "elapsedTime": 0, @@ -2825,6 +2813,1413 @@ "tags": "cell_soap_gui", "isError": false }, + { + "id": "codedb2MCr", + "type": "code", + "evaluator": "IPython", + "input": { + "body": [ + "class NOMADStructure(object):", + " \"\"\"Read the atomic structure and the total energy of a system given a NOMAD", + " JSON file.", + "", + " Gets data from JSON file and sets up the ase.Atoms objects.", + " It handles multiple geometries in the NOMAD file (e.g. configurations", + " from a geometry optimization). ", + "", + " Parameters", + " ----------", + "", + " in_file : string,", + " Path to json file to read", + "", + " frame_list : int, list (or list of lists)", + " Specifies for each NOMAD json file the frames to load.", + " It is a list if only one frame for each json file needs to be", + " loaded, while it is a list of lists otherwise.", + " Negative indeces are supported.", + "", + " png_path : string", + " Path to the folder where the png files for each structure are", + " written.", + "", + " geo_path : string", + " Path to the folder where the png files for each structure are", + " written.", + "", + " png_file : string", + " Path to the png file where the image for each structure and frame", + " is written.", + "", + " geo_file : string", + " Path to the geometry file where the image for each structure and", + " frame is written.", + "", + " xray_path : string", + " Path to the folder where the xray diffraction pattern png files for", + " each structure are written.", + "", + " xray_file : string", + " Path to the xray diffraction pattern png files where the image for", + " each structure and frame is written.", + "", + " isPeriodic : bool", + " Specify if the system is periodic (used for generating periodic", + " replicas in the plot).", + " If `True` if create a 4x4x4 periodic replica of the unit cell for", + " visualization.", + " .. todo:: It should be guessed automatically using", + " `nomad_classify `.", + "", + " file_format : text, optional, {'NOMAD', 'rdf'}", + " Specify what is the format of the file to read.", + " ('rdf' is DEPRECATED).", + "", + "", + " Attributes", + " ----------", + "", + " atoms : dict", + "", + " energy_eV : dict", + "", + " name : (?)", + " Sha - checksum.", + "", + " chemical_symbols : dict", + "", + " chemical_formula : dict", + "", + " spacegroup_analyzer : dict", + " Spacegroup analyzer object of pymatgen", + " http://pymatgen.org/_modules/pymatgen/symmetry/analyzer.html", + "", + "", + " \"\"\"", + "", + " def __init__(", + " self, in_file=None, frame_list=None, png_path=None,", + " png_file=None, geo_path=None, geo_file=None, desc_path=None,", + " rdf_file=None, xray_path=None, xray_file=None, isPeriodic=None,", + " file_format=None, cell_type=None, take_first=True,", + " descriptor=None):", + "", + " self.m_to_ang = 1.0e10", + " self.j_to_ev = 6.241509e18", + " self.atoms = {}", + " self.scaled_positions = {}", + " self.energy_total = {}", + " self.energy_total__eV = {}", + " self.in_file = in_file", + " self.frame_list = frame_list", + " self.png_path = png_path", + " self.png_file = {}", + " self.geo_path = geo_path", + " self.geo_file = {}", + " self.desc_path = desc_path", + " self.xray_path = xray_path", + " self.xray_file = {}", + " self.xray_npy_file = {}", + " self.xray_rs_file = {}", + " self.rdf_file = {}", + " self.name = os.path.splitext(os.path.basename(in_file))[0]", + " self.chemical_symbols = {}", + " self.chemical_formula = {}", + " self.isPeriodic = isPeriodic", + " self.Id = {}", + " self.isEnergyNone = False", + " self.file_format = file_format", + " self.cell_type = cell_type", + " self.spacegroup_analyzer = {}", + " self.spacegroup_analyzer_actual = {}", + " ", + " ", + " if self.file_format is None:", + " self.file_format = 'NOMAD'", + "", + " if self.file_format == 'NOMAD':", + " # read JSON file", + " json_dict = self._get_json_dict(in_file)", + "", + " # get single_config_calc (target: energy_total)", + " single_config_calc = self._get_single_config_calc(json_dict)", + "", + " # extract energy from the list in single_config_calc", + " for (gIndexRun, gIndexSingle), structure in single_config_calc.iteritems():", + " energy = structure.get('energy_total')", + " if energy is None:", + " # logger.warning(", + " # \"Could not find energy_total in \" +", + " # \"single_config_calculations \\n with gIndexSingle {0}\" +", + " # \"in section_run with gIndexRun {1} \\n\" +", + " # \"in file {2}\".format(", + " # gIndexSingle,", + " # gIndexRun,", + " # self.in_file))", + " isEnergyNone = True", + " self.energy_total[gIndexRun, gIndexSingle] = 0.0", + " self.energy_total__eV[gIndexRun, gIndexSingle] = 0.0", + " else:", + " self.energy_total[", + " gIndexRun, gIndexSingle] = energy", + " self.energy_total__eV[", + " gIndexRun, gIndexSingle] = energy * self.j_to_ev", + "", + " # get system_description (target: structure)", + " system_descriptions = self._get_system_descriptions(json_dict)", + "", + " # compare dictionaries of single_config_calc and", + " # system_descriptions", + " logger.debug(\"Single configuration keys: {0}\".format(", + " set(single_config_calc.keys())))", + " logger.debug(\"System description keys: {0}\".format(", + " set(system_descriptions.keys())))", + "", + " intersect = set(single_config_calc.keys()).intersection(", + " set(system_descriptions.keys()))", + " not_intersect = set(single_config_calc.keys()).symmetric_difference(", + " set(system_descriptions.keys()))", + "", + " logger.debug(", + " \"Deleting frames that do not both have 'single_config_calc' and in 'system_descriptions'.\")", + " for key in not_intersect:", + " if key in system_descriptions:", + " del system_descriptions[key]", + " if take_first:", + " logger.debug(", + " \"Keeping only 1st frame in which both 'single_config_calc' and 'system_descriptions' are present.\")", + " not_intersect_system = set([(0, 0)]).symmetric_difference(", + " set(system_descriptions.keys()))", + " not_intersect_single = set([(0, 0)]).symmetric_difference(", + " set(single_config_calc.keys()))", + " index = 0", + " else:", + " logger.debug(", + " \"Keeping only last frame in which both 'single_config_calc' and 'system_descriptions' are present.\")", + " index = len(system_descriptions)-1", + " system_descriptions_value = system_descriptions[(0, index)]", + " system_descriptions.clear()", + " system_descriptions[(0, 0)] = system_descriptions_value", + "", + " single_config_calc_value = single_config_calc[(0, index)]", + " single_config_calc.clear()", + " single_config_calc[(0, 0)] = single_config_calc_value", + " ", + " # print len(single_config_calc)", + " # print len(system_descriptions)", + "", + " # print set(single_config_calc.keys())", + " # print set(system_descriptions.keys())", + "", + " # extract structure data from the list in system_descriptions", + " # the key is a tuple (gIndexRun, gIndexDesc)", + " # Note: self.atoms is a dict with key (gIndexRun, gIndexDesc)", + " # for (gIndexRun, gIndexDesc), structure in", + " # system_descriptions.items():", + " for (gIndexRun, gIndexDesc), structure in system_descriptions.iteritems():", + " # old format", + " # labels = structure.get('atom_label')", + " labels = structure.get('atom_labels')", + "", + " if labels is None:", + " raise Exception(", + " \"Could not find atom_label in section_system_description\" +", + " \"\\nwith gIndex %d in section_run with gIndex \" +", + " \"%d!\" %", + " gIndexDesc %", + " gIndexRun)", + "", + " # positions = structure.get('atom_position')", + " positions = structure.get('atom_positions')", + "", + " if positions is None:", + " raise Exception(", + " \"Could not find atom_position in \" +", + " \"section_system_description \\nwith gIndex %d in\" +", + " \"section_run with gIndex %d!\" % gIndexDesc % gIndexRun)", + "", + " cell = structure.get('simulation_cell')", + "", + " # convert to Angstrom and numpy array", + " positions = self.m_to_ang * np.asarray(positions)", + "", + " # check if all labels are known by ase", + " # if not change unknown label to X", + " for i in range(len(labels)):", + " number = ase.data.atomic_numbers.get(labels[i])", + " if number is None:", + " labels[i] = u'X'", + "", + " if cell is None:", + " self.isPeriodic = False", + " atoms = ase.Atoms(", + " symbols=labels, positions=positions,", + " cell=None, pbc=False)", + " else:", + " self.isPeriodic = True", + " # convert to Angstrom and numpy array", + " cell = self.m_to_ang * np.asarray(cell)", + " # in the metadata, simulation_cell has lattice vectors as", + " # columns, ase has them as rows => transpose", + " atoms = ase.Atoms(", + " symbols=labels, positions=positions,", + "# cell=np.transpose(cell), pbc=True)", + " cell=cell, pbc=True)", + "", + "", + " # get conventional or primitive standard cell with pymatgen", + " if self.cell_type is not None:", + " if self.cell_type == 'primitive':", + " atoms = get_conventional_standard_atoms(atoms)", + " atoms = get_primitive_standard_atoms(atoms)", + " elif self.cell_type == 'standard':", + " atoms = get_conventional_standard_atoms(atoms)", + "", + " # get the SpacegroupAnalyzer object from pymatgen ", + " # for further processing (e.g. to get spacegroup number or symbol)", + " # (from PyMatGen): tolerance of 0.1 (the value used in Materials Project) is often needed", + "# symprecs = np.logspace(-3, -1, 7, endpoint=True, base=10.0).tolist() ", + "# symprecs = np.linspace(1.0E-3, 1E-1, i, endpoint=True).tolist() ", + "# symprecs = [1.0E-3, 1.0E-2, 1.0E-1]", + "# angle_tolerances = [1., 5.]", + "", + " symprecs = [1.0E-3]", + " angle_tolerances = [1.]", + "", + " spacegroup_analyzer = {} ", + " # build a dictionary with different spacegroup analyzers according", + " # to the thresholds used", + " try:", + " for symprec in symprecs:", + " for angle_tolerance in angle_tolerances:", + " spacegroup_analyzer[symprec, angle_tolerance] = SpacegroupAnalyzer(AseAtomsAdaptor.get_structure(atoms),", + "# symprec=1e-1, angle_tolerance=5) ", + " symprec=symprec, angle_tolerance=angle_tolerance) ", + " except:", + " spacegroup_analyzer=None", + " ", + " # wrap atomic positions inside unit cell", + " atoms.wrap()", + " # save the atoms", + " self.Id[gIndexRun, gIndexDesc] = (gIndexRun, gIndexDesc)", + " self.atoms[gIndexRun, gIndexDesc] = atoms", + " # get chemical formula", + " self.chemical_formula[", + " gIndexRun,", + " gIndexDesc] = atoms.get_chemical_formula(", + " mode='hill')", + " self.chemical_symbols[", + " gIndexRun, gIndexDesc] = atoms.get_chemical_symbols()", + " self.scaled_positions[", + " gIndexRun,", + " gIndexDesc] = atoms.get_scaled_positions(", + " wrap=True)", + " ", + " self.spacegroup_analyzer[", + " gIndexRun,", + " gIndexDesc] = spacegroup_analyzer", + " ", + "", + " elif self.file_format == 'xyz':", + " ''' reads xyz file with a list of configurations'''", + " xyz_file = open(self.in_file, 'r')", + "", + " try:", + " ase_frames = ase.io.read(self.in_file, index=':', format='xyz')", + " logger.debug(", + " \"Number of frames found: {0}\".format(", + " len(ase_frames)))", + "", + " N_frames = len(ase_frames)", + "", + " # usually the frame list is not defined in this cases", + " if frame_list is None:", + " frame_list = range(N_frames)", + "", + " # check if frame_list is actually a list and not only a number", + " if isinstance(frame_list, list) is False:", + " frame_list = [frame_list]", + "", + " for frame in frame_list:", + "", + " atoms = ase_frames[frame]", + "", + " # wrap atomic positions inside unit cell", + " atoms.wrap()", + "", + " # save the atoms", + " self.atoms[0, frame] = atoms", + "", + " # instead of chemical formula, display the name", + " self.chemical_formula[", + " 0, frame] = atoms.get_chemical_formula(", + " mode='hill')", + " self.energy_total__eV[0, frame] = 0.0", + " self.energy_total[0, frame] = 0.0", + "", + "", + " # it is the same as self.gIndexDescMax = i", + " self.gIndexRunMax = 0", + " self.gIndexDescMax = len(frame_list) - 1", + "", + " finally:", + " xyz_file.close()", + "", + " else:", + " logger.error(", + " \"Please specify if the file is a JSON file is either a file \\nfrom the NOMAD repository or a Radial Distribution Function\")", + "", + " def __getitem__(self, index):", + " return self.energy_total[index], self.png_file[index], self.geo_file[index], self.chemical_formula[index], self.name", + "", + " def __len__(self):", + " return self._data_len", + "", + " def _get_json_dict(self, in_file):", + " \"\"\"Reads JSON content from file.", + " Args:", + " in_file: file which is read.", + " Returns:", + " Dictionary loaded from JSON file.", + " \"\"\"", + " try:", + " with open(in_file) as json_file:", + " try:", + " return json.load(json_file)", + " except Exception:", + " logger.error(", + " \"Could not read content from JSON file '%s'! See below for error message.\" %", + " in_file)", + " raise", + " finally:", + " json_file.close()", + " except IOError:", + " raise Exception(\"Could not open file '%s'!\" % in_file)", + "", + " def _get_system_descriptions(self, json_dict):", + " \"\"\"Extract section_system_description from JSON dictionary (to obtain the structure in this case)", + " Args:", + " json_dict: JSON dictionary containing parsed data.", + " Returns:", + " Dictionaries of section_system_description for each section_run as dictionary.", + " The keys are a tuple (gIndexRun, gIndexDesc) of the different section_run and section_system_description, respectively.", + " \"\"\"", + "", + " # old format", + " # for section in sections", + "", + " found_section_run = False", + " sections = json_dict.get('sections')", + " section_system_descriptions = {}", + "", + " # read section_run and for each section_run read section_system_description", + " # gIndexRun: gIndex for section_run", + " # gIndexDesc: gIndex for section_system_description", + " if sections is not None:", + " for section in sections.values():", + " if section.get('name') == 'section_run':", + " found_section_run = True", + " section_run_sections = section.get('sections')", + " gIndexRun = section.get('gIndex')", + " if section_run_sections is not None and gIndexRun is not None:", + " # extract all occurrences of section_system_description", + " for section_run_section in section_run_sections.values():", + " if section_run_section.get(", + " 'name') == 'section_system':", + " # if section_run_section.get('name') ==", + " # 'section_system_description':", + " found_section_system_description = True", + " gIndexDesc = section_run_section.get('gIndex')", + " section_system_descriptions[", + " gIndexRun, gIndexDesc] = section_run_section", + " else:", + " raise Exception(\"Could not find key 'sections' or 'gIndex' in section_run!\")", + "", + " if not found_section_run:", + " raise Exception(\"Could not find any section_run!\")", + " else:", + " raise Exception(\"Could not find key 'sections' in JSON file!\")", + "", + " self.gIndexRunMax = gIndexRun", + " self.gIndexDescMax = gIndexDesc", + " return section_system_descriptions", + "", + " def _get_single_config_calc(self, json_dict):", + " \"\"\"Extract _get_single_config_calc from JSON dictionary (to obtain the energy in this case).", + " It is the analogue of ' _get_system_descriptions', but for the single_config_calc section.", + " Args:", + " json_dict: JSON dictionary containing parsed data.", + " Returns:", + " Dictionaries of _get_single_config_calc for each section_run as dictionary.", + " The keys are a tuple (gIndexRun, gIndexSingle) of the different section_run and section_single_configuration_calculation, respectively.", + " \"\"\"", + "", + " # old format", + " # for section in sections", + "", + " found_section_run = False", + " sections = json_dict.get('sections')", + " section_single_config_calc = {}", + "", + " # read section_run and for each section_run read section_system_description", + " # gIndexRun: gIndex for section_run", + " # gIndexDesc: gIndex for single_config_calc", + "", + " if sections is not None:", + " for section in sections.values():", + " if section.get('name') == 'section_run':", + " found_section_run = True", + " section_run_sections = section.get('sections')", + " gIndexRun = section.get('gIndex')", + "", + " if section_run_sections is not None and gIndexRun is not None:", + " # extract all occurrences of", + " # section_single_configuration_calculation", + " for section_run_section in section_run_sections.values():", + " if section_run_section.get(", + " 'name') == 'section_single_configuration_calculation':", + " found_section_single_configuration_calculation = True", + " gIndexSingle = section_run_section.get(", + " 'gIndex')", + " section_single_config_calc[", + " gIndexRun, gIndexSingle] = section_run_section", + " else:", + " raise Exception(", + " \"Could not find key 'sections' or 'gIndex' in section_run!\")", + " if not found_section_run:", + " raise Exception(\"Could not find any section_run!\")", + " else:", + " raise Exception(\"Could not find key 'sections' in JSON file!\")", + " return section_single_config_calc", + "", + " def write_geometry(", + " self,", + " path=None,", + " filename_suffix='_aims.in',", + " format='aims',", + " operation_number=0):", + " \"\"\"Writes the coordinates of the structure as text file with the writing routine of ASE.", + "", + " Parameters", + " ----------", + " path : string, optional, default `geo_path`", + " Path to the folder where the geometry files are written", + "", + " filename_suffix : string, default '_aims.in'", + " Suffix added after filename", + "", + " format : string, optional, default 'aims'", + " Format of the file to be written. Must be a valid ASE format", + " (see https://wiki.fysik.dtu.dk/ase/ase/io/io.html#module-ase.io)", + "", + " \"\"\"", + " # define the default path as geo_path", + " if path is None:", + " path = self.geo_path", + "", + " if self.file_format == 'NOMAD':", + " for (gIndexRun, gIndexDesc), atoms in self.atoms.items():", + " if atoms is not None:", + " # filename is the normalized absolute path", + " filename = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s_%d_%d_op%d%s' %", + " (self.name, gIndexRun, gIndexDesc, operation_number, filename_suffix))))", + " ", + " atoms.write(filename, format=format)", + "", + " # store the normalized absolute path to the geometry file", + " # in the class", + " if configs[\"isBeaker\"] == \"True\":", + "# if False:", + " # only for Beaker Notebook", + " filename = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " '/user/tmp/', '%s_%d_%d_op%d%s' %", + " (self.name, gIndexRun, gIndexDesc, operation_number, filename_suffix))))", + " else:", + " # to run locally", + " filename = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s_%d_%d_op%d%s' %", + " (self.name, gIndexRun, gIndexDesc, operation_number, filename_suffix))))", + "", + " self.geo_file[gIndexRun, gIndexDesc] = filename", + "", + "", + " else:", + " raise Exception(", + " \"Please specify a valid file format. Possible file formats are 'NOMAD' or 'rdf'.\")", + "", + " def write_png(", + " self,", + " path=None,", + " filename_suffix='.png',", + " replicas=None,", + " rotation=None,", + " operation_number=0):", + " ", + " \"\"\"Write png images for the structures read from the JSON files. Builds a 4x4x4 supercell", + " if the structure is periodic.", + "", + "", + " Parameters", + " ----------", + " path : string, optional, default `png_path`", + " Path to the folder where the geometry files are written", + "", + " filename_suffix : string, default '.png'", + " Suffix added after filename", + "", + " replicas: list of 3 integers, default [4,4,4]", + " Number of replicas in each direction. Used only if `isPeriodic` is `True`.", + "", + " \"\"\"", + " # define the default path as geo_path", + " if path is None:", + " path = self.png_path", + "", + " if rotation:", + " rot = '10z,-80x'", + " else:", + " rot = '0x, 0y, 0z'", + "", + " filename_list = []", + "", + " if self.file_format == 'NOMAD':", + " for (gIndexRun, gIndexDesc), atoms in self.atoms.items():", + " if atoms is not None:", + " # filename is the normalized absolute path", + " filename = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s_%d_%d_op%d_geometry_thumbnail%s' %", + " (self.name, gIndexRun, gIndexDesc, operation_number, filename_suffix))))", + "", + " # if it is periodic, replicate according to the vector", + " # replicas", + " if self.isPeriodic:", + " # set the default to 4 replicas in each direction", + " if replicas is None:", + " replicas = (4, 4, 4)", + " else:", + " replicas = (1, 1, 1)", + "", + " atoms = atoms * replicas", + "", + " # View used to start ag, and find desired viewing angle", + " # rot = '35x,63y,36z' # found using ag: 'view -> rotate'", + "", + " # Common kwargs for eps, png, pov", + " kwargs = {", + " # text string with rotation (default='' )", + " 'rotation': rot,", + " 'radii': .50, # float, or a list with one float per atom", + " 'colors': None, # List: one (r, g, b) tuple per atom", + " 'show_unit_cell': 0, # 0, 1, or 2 to not show, show, and show all of cell", + " 'scale': 100,", + " }", + "", + " atoms.write(filename, format='png', **kwargs)", + "", + " if configs[\"isBeaker\"] == \"True\":", + " # only for Beaker Notebook", + " filename = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " '/user/tmp/', '%s_%d_%d_op%d_geometry_thumbnail%s' %", + " (self.name, gIndexRun, gIndexDesc, operation_number, filename_suffix))))", + " else:", + " # to run locally", + " filename = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s_%d_%d_op%d_geometry_thumbnail%s' %", + " (self.name, gIndexRun, gIndexDesc, operation_number, filename_suffix))))", + "", + " # store the normalized absolute path to the png file in the", + " # class", + " self.png_file[gIndexRun, gIndexDesc] = filename", + "", + " filename_list.append(filename)", + "", + " else:", + " logger.error(\"Could not find atoms in %s\" % self.name)", + "", + " else:", + " logger.error(", + " \"Please specify a valid file format. Possible formats are 'NOMAD' or 'rdf'.\")", + " ", + " return filename_list", + "", + "", + " def _calc_rdf(self, gIndexRun, gIndexDesc, maxR, is_prdf=None):", + " \"\"\"Returns the radial distribution function of a single (user specified) frame given a NOMADstructure.", + " This function was written by Fawzi Mohamed.", + " Args:", + " gIndexRun: int. run index of the frame (usually 0)", + " gIndexDesc: int. system_description index of the frame", + " maxR: float. cut-off radius up to which the atom distances are considered", + " is_prdf: bool. If true calculates partial radial distribution function.", + " If false calculates radial distribution function (all atom types are the same)", + " Returns:", + " radD: radial distribution function for a single frame with gIndexRun=gIndexRun and gIndexDesc=gIndexDesc", + " Note:", + " cell vectors v1,v2,v3 with values in the columns: [[v1x,v2x,v3x],[v1y,v2y,v3x],[v1z,v2z,v3z]]", + " \"\"\"", + " if is_prdf is None:", + " is_prdf = True", + "", + " if self.isPeriodic:", + " # in the metadata, the simulation_cell has lattice vectors as columns, ASE has them as rows", + " # in the NOMADstructure the cell has been trasposed from the metadata => lattice vectors are as rows", + " # calc_rdf needs lattice vectors as colulmns => transpose again", + " cell = self.atoms[gIndexRun, gIndexDesc].get_cell()", + "# cell = np.transpose(cell)", + " atoms = self.atoms[gIndexRun, gIndexDesc]", + " positions = self.atoms[", + " gIndexRun,", + " gIndexDesc].get_positions(", + " wrap=True)", + " maxR2 = maxR * maxR", + "", + " radD = {}", + " for ii, a1 in enumerate(atoms):", + " for jj, a2 in enumerate(atoms[ii:]):", + "", + " # write atomic numbers if prdf, otherwise set them to zero", + " if is_prdf:", + " n1 = a1.number", + " n2 = a2.number", + " else:", + " n1 = 0", + " n2 = 0", + "", + " label = \"%d_%d\" % (min(n1, n2), max(n1, n2))", + " if label not in radD:", + " radD[label] = {", + " \"particle_atom_numer_1\": n1,", + " \"particle_atom_numer_2\": n2,", + " \"arr\": []", + " }", + " arr = radD[label][\"arr\"]", + " r0 = np.array([a1.x - a2.x, a1.y - a2.y, a1.z - a2.z])", + " r02 = np.dot(r0, r0)", + " r = r02 - maxR2", + " m = np.dot(cell.transpose(), cell)", + " l = np.dot(r0, cell)", + " r = np.dot(r0, r0) - maxR2", + " mii = m[0, 0]", + " mij = m[0, 1]", + " mik = m[0, 2]", + " mjj = m[1, 1]", + " mjk = m[1, 2]", + " mkk = m[2, 2]", + " li = l[0]", + " lj = l[1]", + " lk = l[2]", + " c = (", + " mjj**2 *", + " mkk**3 *", + " r -", + " 2 *", + " mjj *", + " mjk**2 *", + " mkk**2 *", + " r +", + " mjk**4 *", + " mkk *", + " r -", + " lj**2 *", + " mjj *", + " mkk**3 +", + " lj**2 *", + " mjk**2 *", + " mkk**2 +", + " 2 *", + " lj *", + " lk *", + " mjj *", + " mjk *", + " mkk**2 -", + " lk**2 *", + " mjj**2 *", + " mkk**2 -", + " 2 *", + " lj *", + " lk *", + " mjk**3 *", + " mkk +", + " lk**2 *", + " mjj *", + " mjk**2 *", + " mkk)", + " a = (", + " mii *", + " mjj**2 *", + " mkk**3 -", + " mij**2 *", + " mjj *", + " mkk**3 -", + " 2 *", + " mii *", + " mjj *", + " mjk**2 *", + " mkk**2 +", + " mij**2 *", + " mjk**2 *", + " mkk**2 +", + " 2 *", + " mij *", + " mik *", + " mjj *", + " mjk *", + " mkk**2 -", + " mik**2 *", + " mjj**2 *", + " mkk**2 +", + " mii *", + " mjk**4 *", + " mkk -", + " 2 *", + " mij *", + " mik *", + " mjk**3 *", + " mkk +", + " mik**2 *", + " mjj *", + " mjk**2 *", + " mkk)", + " b = (", + " 2 *", + " li *", + " mjj**2 *", + " mkk**3 -", + " 2 *", + " lj *", + " mij *", + " mjj *", + " mkk**3 -", + " 4 *", + " li *", + " mjj *", + " mjk**2 *", + " mkk**2 +", + " 2 *", + " lj *", + " mij *", + " mjk**2 *", + " mkk**2 +", + " 2 *", + " lj *", + " mik *", + " mjj *", + " mjk *", + " mkk**2 +", + " 2 *", + " lk *", + " mij *", + " mjj *", + " mjk *", + " mkk**2 -", + " 2 *", + " lk *", + " mik *", + " mjj**2 *", + " mkk**2 +", + " 2 *", + " li *", + " mjk**4 *", + " mkk -", + " 2 *", + " lj *", + " mik *", + " mjk**3 *", + " mkk -", + " 2 *", + " lk *", + " mij *", + " mjk**3 *", + " mkk +", + " 2 *", + " lk *", + " mik *", + " mjj *", + " mjk**2 *", + " mkk)", + "", + " delta = b * b - 4 * a * c", + "", + " if (a == 0 or delta < 0):", + " continue", + " sDelta = math.sqrt(delta)", + " imin = int(math.ceil((-b - sDelta) / (2 * a)))", + " imax = int(math.floor((-b + sDelta) / (2 * a)))", + " for i in range(imin, imax + 1):", + " cj = (mkk * r + i**2 * mii * mkk + 2 * i * li *", + " mkk - i**2 * mik**2 - 2 * i * lk * mik - lk**2)", + " aj = (mjj * mkk - mjk**2)", + " bj = (2 * i * mij * mkk + 2 * lj * mkk -", + " 2 * i * mik * mjk - 2 * lk * mjk)", + " deltaj = bj * bj - 4 * aj * cj", + " if (aj == 0 or deltaj < 0):", + " continue", + " sDeltaj = math.sqrt(deltaj)", + " jmin = int(math.ceil((-bj - sDeltaj) / (2 * aj)))", + " jmax = int(math.floor((-bj + sDeltaj) / (2 * aj)))", + " for j in range(jmin, jmax + 1):", + " ck = r + j**2 * mjj + 2 * i * j * mij + i**2 * mii + 2 * j * lj + 2 * i * li", + " ak = mkk", + " bk = (2 * j * mjk + 2 * i * mik + 2 * lk)", + " deltak = bk * bk - 4 * ak * ck", + " if (ak == 0 or deltak < 0):", + " continue", + " sDeltak = math.sqrt(deltak)", + " kmin = int(math.ceil((-bk - sDeltak) / (2 * ak)))", + " kmax = int(math.floor((-bk + sDeltak) / (2 * ak)))", + " for k in range(kmin, kmax + 1):", + " if (jj != 0 or i != 0 or j != 0 or k != 0):", + " rr = r02 + k**2 * mkk + k * \\", + " (2 * j * mjk + 2 * i * mik + 2 * lk) + j**2 * mjj + 2 * i * j * mij + i**2 * mii + 2 * j * lj + 2 * i * li", + " arr.append(math.sqrt(rr))", + " wFact = 4 * math.pi * len(atoms) / abs(np.linalg.det(cell))", + " for k, v in radD.items():", + " v[\"arr\"].sort()", + " v[\"weights\"] = map(lambda r: 1.0 / (wFact * r * r), v[\"arr\"])", + " return radD", + "", + " def write_rdf(", + " self,", + " path=None,", + " filename_suffix='.json',", + " maxR=None,", + " is_prdf=None):", + " \"\"\"Write a JSON file with structure info and radial distribution functions of all the frames in the NOMADstructure", + "", + " One json file is generated for each NOMADjson file. If the NOMADjson file contains multiple frames,", + " the partial radial distribution functions of different frames are appended.", + "", + " Parameters", + " ----------", + " path : string", + " Path to the folder where the rdf file is written", + "", + " filename_suffix : string, default '.json'", + " Suffix added after filename (the filename is the NoMaD database unique identifier)", + "", + " replicas : list of 3 integers, default [4,4,4]", + " Number of replicas in each direction. Used only if `isPeriodic` is `True`.", + "", + " maxR : float, default 25", + " Cut-off radius in Angstrom up to which the atom distances are considered", + "", + " .. todo:: Add BIN_COUNT to parameters.", + "", + " is_prdf : bool, default `True`", + " If `True` calculates partial radial distribution function.", + " If `False` calculates radial distribution function (all atom types are the same)", + "", + "", + " Returns", + " -------", + "", + " filename : string", + " Absolute path where the file with the partial radial distribution function(s) is written.", + "", + "", + " \"\"\"", + "", + " if self.isPeriodic:", + " filename = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s%s' %", + " (self.name, filename_suffix))))", + " self.rdf_file = filename", + " outF = file(filename, 'w')", + " outF.write(\"\"\"", + " {", + " \"data\":[\"\"\")", + "", + " for (gIndexRun, gIndexDesc), atoms in self.atoms.items():", + " if atoms is not None:", + " # filename is the normalized absolute path", + " # filename = os.path.abspath(os.path.normpath(os.path.join(path, '%s_%d_%d%s' % (self.name, gIndexRun, gIndexDesc, filename_suffix))))", + " # store the normalized absolute path to the rdf file in the class", + " # self.rdf_file[gIndexRun, gIndexDesc] = filename", + "", + " cell = self.atoms[gIndexRun, gIndexDesc].get_cell()", + "# cell = np.transpose(cell)", + " atoms = self.atoms[gIndexRun, gIndexDesc]", + " positions = self.atoms[", + " gIndexRun, gIndexDesc].get_positions(", + " wrap=True)", + " energy_total__eV = self.energy_total__eV[gIndexRun, gIndexDesc]", + " energy_total = self.energy_total[gIndexRun, gIndexDesc]", + "", + " writeColon = False", + "", + " rdf = self._calc_rdf(", + " gIndexRun=gIndexRun,", + " gIndexDesc=gIndexDesc,", + " maxR=25,", + " is_prdf=is_prdf)", + " res = {", + " \"calc_id\": 'NaN',", + " \"checksum\": self.name,", + " \"energy_total\": energy_total,", + " \"energy_total__eV\": energy_total__eV,", + " \"path\": self.rdf_file,", + " \"step\": gIndexDesc,", + " \"final\": 'NaN',", + " \"struct_id\": 'NaN',", + " \"cell\": cell.tolist(),", + " \"particle_atom_number\": map(", + " lambda x: x.number,", + " atoms),", + " \"particle_position\": map(", + " lambda x: [", + " x.x,", + " x.y,", + " x.z],", + " atoms),", + " \"radial_distribution_function\": rdf}", + " if (writeColon):", + " outF.write(\", \")", + " writeColon = True", + " json.dump(res, outF, indent=2)", + " outF.write(\"\"\"", + " ] }\"\"\")", + " outF.flush()", + "", + " else:", + " raise Exception(", + " \"File {0} is a non-periodic structure. The radial distribution function is \\ncurrently implemented only for periodic systems.\".format(self.in_file))", + "", + " # only 1 filename because all the frames are in the same file", + " return filename", + "", + " def write_xray(", + " self,", + " path=None,", + " filename_suffix='_xray.png',", + " replicas=None,", + " grayscale=True,", + " user_param_source=None,", + " user_param_detector=None,", + " rotation=None,", + " angles_d=None):", + " \"\"\"Write xray images for the structures read from the JSON files. Builds a 4x4x4 supercell", + " if the structure is periodic.", + "", + " Parameters", + " ----------", + " path : string, optional, default `xray_path`", + " Path to the folder where the xray files are written", + "", + " filename_suffix : string, default '_xray.png'", + " Suffix added after filename", + "", + " replicas: list of 3 integers, default [4,4,4]", + " Number of replicas in each direction. Used only if `isPeriodic` is `True`.", + "", + " Returns", + " -------", + "", + " filename_list : string or list", + " Xray file (or list of xray files) generated from the file. It is a list if multiple", + " frames are present.", + "", + " \"\"\"", + "", + " filename_list = []", + "", + " # define the default path as xray_path", + " if path is None:", + " path = self.xray_path", + "", + " param_source = {", + " 'wavelength': 1.0E-11,", + " 'pulse_energy': 1.6022e-14,", + " 'focus_diameter': 1E-6", + " }", + "", + " param_detector = {", + " 'distance': 0.10,", + " 'pixel_size': 16E-5,", + " 'nx': 28,", + " 'ny': 28", + " }", + "", + " if user_param_source is not None:", + " param_source.update(user_param_source)", + "", + " if user_param_detector is not None:", + " param_detector.update(user_param_detector)", + "", + " if not rotation:", + " angles_d = [0.0]", + "", + " # logger.debug(\"Source parameters \\n {0}\".format(param_source))", + " # logger.debug(\"Detector parameters \\n {0}\".format(param_source))", + "", + " if (self.file_format == 'NOMAD') or (self.file_format == 'xyz'):", + " for (gIndexRun, gIndexDesc), atoms in self.atoms.items():", + " if atoms is not None:", + "", + " # if it is periodic, replicate according to the vector", + " # replicas", + " if self.isPeriodic:", + " # set the default to 4 replicas in each direction", + " if replicas is None:", + " replicas = (4, 4, 4)", + " else:", + " replicas = (1, 1, 1)", + "", + " atoms = atoms * replicas", + "", + " # Source", + " src = condor.Source(**param_source)", + "", + " # Detector", + " det = condor.Detector(**param_detector)", + "", + " # Atoms", + " atomic_numbers = map(lambda x: x.number, atoms)", + "", + " # convert Angstrom to m (CONDOR uses meters)", + " atomic_positions = map(", + " lambda x: [", + " x.x * 1E-10,", + " x.y * 1E-10,", + " x.z * 1E-10],", + " atoms)", + "", + " for angle_d in angles_d:", + " # filename is the normalized absolute path", + " filename_xray = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s_%d_%d_%d%s' %", + " (self.name, gIndexRun, gIndexDesc, angle_d, filename_suffix))))", + " filename_rs = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s_%d_%d_%d%s' %", + " (self.name, gIndexRun, gIndexDesc, angle_d, '_xray_rs.png'))))", + " filename_ph = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s_%d_%d_%d%s' %", + " (self.name, gIndexRun, gIndexDesc, angle_d, '_xray_ph.png'))))", + " filename_npy = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s_%d_%d_%d%s' %", + " (self.name, gIndexRun, gIndexDesc, angle_d, '.npy'))))", + "", + " angle = angle_d / 360. * 2 * np.pi", + " rotation_axis = np.array([0., 0., 1.])/np.sqrt(1.)", + " #rotation_axis = np.array([1., 1., 1.]) / np.sqrt(3.)", + " quaternion = condor.utils.rotation.quat(", + " angle, rotation_axis[0], rotation_axis[1], rotation_axis[2])", + " rotation_values = np.array([quaternion])", + " rotation_formalism = \"quaternion\"", + " rotation_mode = \"extrinsic\"", + "", + " par = condor.ParticleAtoms(", + " atomic_numbers=atomic_numbers,", + " atomic_positions=atomic_positions,", + " rotation_values=rotation_values,", + " rotation_formalism=rotation_formalism,", + " rotation_mode=rotation_mode)", + "", + " s = \"particle_atoms\"", + " E = condor.Experiment(src, {s: par}, det)", + " res = E.propagate()", + "", + " real_space = np.fft.fftshift(", + " np.fft.ifftn(", + " np.fft.fftshift(", + " res[\"entry_1\"][\"data_1\"][\"data_fourier\"])))", + " intensity_pattern = res[\"entry_1\"][\"data_1\"][\"data\"]", + " fourier_space = res[\"entry_1\"][", + " \"data_1\"][\"data_fourier\"]", + " phases = np.angle(fourier_space) % (2 * np.pi)", + " # vmin = np.log10(res[\"entry_1\"][\"data_1\"][\"data\"].max()/10000.)", + "", + " # scaler = preprocessing.StandardScaler().fit(intensity_pattern)", + " # intensity_pattern = scaler.transform(intensity_pattern)", + "", + " # intensity_pattern = np.log10(intensity_pattern)", + "", + " # real space image", + " # np.save(filename_npy, rs8)", + "", + " if grayscale:", + " I8 = (((intensity_pattern -", + " intensity_pattern.min()) /", + " (intensity_pattern.max() -", + " intensity_pattern.min())) *", + " 255.0).astype(np.uint8)", + " rs8 = (((real_space -", + " real_space.min()) /", + " (real_space.max() -", + " real_space.min())) *", + " 255.0).astype(np.uint8)", + " ph8 = (((phases - phases.min()) / (phases.max() -", + " phases.min())) * 255.0).astype(np.uint8)", + "", + " img = Image.fromarray(I8)", + " img.save(filename_xray)", + "", + " img = Image.fromarray(rs8)", + " img.save(filename_rs)", + "", + " img = Image.fromarray(ph8)", + " img.save(filename_ph)", + "", + " np.save(filename_npy, I8)", + " # np.save(filename_npy, ph8)", + "", + " else:", + " pypl.imsave(", + " filename_xray, np.log10(intensity_pattern))", + " np.save(filename_npy, intensity_pattern)", + " # pypl.imsave(filename_xray, np.log10(intensity_pattern), vmin=vmin)", + " pypl.imsave(filename_ph, phases)", + " pypl.imsave(filename_rs, abs(real_space))", + "", + "# the Viewer with xray files will not work", + "# if configs[\"isBeaker\"] == \"True\":", + "# # only for Beaker Notebook", + "# filename_xray = os.path.abspath(", + "# os.path.normpath(", + "# os.path.join(", + "# '/user/tmp/', '%s_%d_%d_%d%s' %", + "# (self.name, gIndexRun, gIndexDesc, angle_d, filename_suffix))))", + "", + " # store the normalized absolute path to the png file in", + " # the class", + " self.xray_file[gIndexRun, gIndexDesc] = filename_xray", + " self.xray_npy_file[", + " gIndexRun, gIndexDesc] = filename_npy", + " self.xray_rs_file[gIndexRun, gIndexDesc] = filename_rs", + "", + " filename_list.append(filename_xray)", + " filename_list.append(filename_npy)", + " filename_list.append(filename_rs)", + "", + " else:", + " raise Exception(\"Could not find atoms in %s\" % self.name)", + "", + " else:", + " raise Exception(", + " \"Please specify a valid file format. Possible format is 'NOMAD'.\")", + "", + " return filename_list", + "", + " def write_target_values(self, path=None, filename_suffix='_target.json',", + " target=None, operation_number=0):", + " \"\"\"Write target values. One file for each frame.", + " The target works only if one frame is considered. Please check.", + "", + " Parameters", + " ----------", + " path : string, optional, default `xray_path`", + " Path to the folder where the geometry files are written", + "", + " filename_suffix : string, default '_target.json'", + " Suffix added after filename", + "", + " \"\"\"", + "", + " filename_list = []", + "", + " # define the default path as xray_path", + " if path is None:", + " path = self.xray_path", + "", + " if (self.file_format == 'NOMAD') or (self.file_format == 'xyz'):", + " for (gIndexRun, gIndexDesc), atoms in self.atoms.items():", + " if atoms is not None:", + " # filename is the normalized absolute path", + " filename = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s_%d_%d_op%d%s' %", + " (self.name, gIndexRun, gIndexDesc, operation_number, filename_suffix))))", + "", + "", + " outF = file(filename, 'w')", + "", + " outF.write(\"\"\"", + " {", + " \"data\":[\"\"\")", + "", + " chemical_formula = self.chemical_formula[", + " gIndexRun, gIndexDesc]", + " cell = self.atoms[gIndexRun, gIndexDesc].get_cell()", + "# cell = np.transpose(cell)", + " atoms = self.atoms[gIndexRun, gIndexDesc]", + " energy_total__eV = self.energy_total__eV[gIndexRun, gIndexDesc]", + " energy_total = self.energy_total[gIndexRun, gIndexDesc]", + " ", + " spacegroup_symbol = {}", + " spacegroup_number = {}", + " pointgroup_symbol = {}", + " crystal_system = {}", + " lattice_type = {}", + " hall_symbol = {}", + " lattice_centering = {}", + "", + " spacegroup_symbol_actual = {}", + " spacegroup_number_actual = {}", + " pointgroup_symbol_actual = {}", + " crystal_system_actual = {}", + " lattice_type_actual = {}", + " hall_symbol_actual = {}", + " lattice_centering_actual = {}", + " ", + " # calculate the actual spacegroup of the defective struture", + " # get the SpacegroupAnalyzer object from pymatgen ", + " symprecs = [1.0E-3, 1.0E-2, 1.0E-1]", + " angle_tolerances = [1., 5.]", + " ", + " spacegroup_analyzer_actual = {} ", + " # build a dictionary with different spacegroup analyzers according", + " # to the thresholds used", + " ", + " for symprec in symprecs:", + " for angle_tolerance in angle_tolerances:", + " spacegroup_analyzer_actual[symprec, angle_tolerance] = SpacegroupAnalyzer(AseAtomsAdaptor.get_structure(atoms),", + " symprec=symprec, angle_tolerance=angle_tolerance) ", + " ", + " self.spacegroup_analyzer_actual[gIndexRun, gIndexDesc] = spacegroup_analyzer_actual", + "# self.spacegroup_analyzer_actual[gIndexRun, gIndexDesc] = self.spacegroup_analyzer[gIndexRun, gIndexDesc] ", + " ", + " # read the dictionary with different spacegroup analyzers ", + " # according to the thresholds", + " # this is for the pristine parental structure", + " for key in self.spacegroup_analyzer[gIndexRun, gIndexDesc]:", + " symprec, angle_tolerance = key ", + " spacegroup_symbol[str(key)] = self.spacegroup_analyzer[gIndexRun, gIndexDesc][key].get_space_group_symbol() ", + " spacegroup_number[str(key)] = self.spacegroup_analyzer[gIndexRun, gIndexDesc][key].get_space_group_number() ", + " pointgroup_symbol[str(key)] = self.spacegroup_analyzer[gIndexRun, gIndexDesc][key].get_point_group_symbol() ", + " crystal_system[str(key)] = self.spacegroup_analyzer[gIndexRun, gIndexDesc][key].get_crystal_system() ", + " # Get the lattice for the structure, e.g., (triclinic, orthorhombic, cubic, etc.).", + " #This is the same than the crystal system with the exception of the", + " #hexagonal/rhombohedral lattice", + " lattice_type[str(key)] = self.spacegroup_analyzer[gIndexRun, gIndexDesc][key].get_lattice_type() ", + " hall_symbol[str(key)] = self.spacegroup_analyzer[gIndexRun, gIndexDesc][key].get_hall() ", + " lattice_centering[str(key)] = self.spacegroup_analyzer[gIndexRun, gIndexDesc][key].get_space_group_symbol()[0] ", + "", + " spacegroup_symbol_actual[str(key)] = self.spacegroup_analyzer_actual[gIndexRun, gIndexDesc][key].get_space_group_symbol() ", + " spacegroup_number_actual[str(key)] = self.spacegroup_analyzer_actual[gIndexRun, gIndexDesc][key].get_space_group_number() ", + " pointgroup_symbol_actual[str(key)] = self.spacegroup_analyzer_actual[gIndexRun, gIndexDesc][key].get_point_group_symbol() ", + " crystal_system_actual[str(key)] = self.spacegroup_analyzer_actual[gIndexRun, gIndexDesc][key].get_crystal_system() ", + " # Get the lattice for the structure, e.g., (triclinic, orthorhombic, cubic, etc.).", + " #This is the same than the crystal system with the exception of the", + " #hexagonal/rhombohedral lattice", + " lattice_type_actual[str(key)] = self.spacegroup_analyzer_actual[gIndexRun, gIndexDesc][key].get_lattice_type() ", + " hall_symbol_actual[str(key)] = self.spacegroup_analyzer_actual[gIndexRun, gIndexDesc][key].get_hall() ", + " lattice_centering_actual[str(key)] = self.spacegroup_analyzer_actual[gIndexRun, gIndexDesc][key].get_space_group_symbol()[0] ", + " ", + " ", + " ", + " writeColon = False", + "", + " res = {", + " \"checksum\": self.name,", + " \"main_json_file_name\": self.in_file,", + " \"chemical_formula\": chemical_formula,", + " \"energy_total__eV\": energy_total__eV,", + " \"energy_total\": energy_total,", + " \"gIndexRun\": gIndexRun,", + " \"gIndexDesc\": gIndexDesc,", + " \"cell\": cell.tolist(),", + " \"particle_atom_number\": map(", + " lambda x: x.number,", + " atoms),", + " \"particle_position\": map(", + " lambda x: [", + " x.x,", + " x.y,", + " x.z],", + " atoms),", + " \"filename\": filename,", + " \"target\": target,", + " ", + " # these are dictionaries with key: (symprec, angle_tolerance)", + " \"spacegroup_symbol\": spacegroup_symbol,", + " \"spacegroup_number\": spacegroup_number,", + " \"pointgroup_symbol\": pointgroup_symbol,", + " \"crystal_system\": crystal_system,", + " \"hall_symbol\": hall_symbol,", + " \"lattice_type\": lattice_type,", + " \"lattice_centering\": lattice_centering,", + "", + " \"spacegroup_symbol_actual\": spacegroup_symbol_actual,", + " \"spacegroup_number_actual\": spacegroup_number_actual,", + " \"pointgroup_symbol_actual\": pointgroup_symbol_actual,", + " \"crystal_system_actual\": crystal_system_actual,", + " \"hall_symbol_actual\": hall_symbol_actual,", + " \"lattice_type_actual\": lattice_type_actual,", + " \"lattice_centering_actual\": lattice_centering_actual,", + "", + " ", + "# \"Bravais_lattice_cs\": crystal_system+lattice_centering,", + "# \"Bravais_lattice_lt\": lattice_type+lattice_centering,", + " ", + " #\"symmetry_dataset\": symmetry_dataset,", + " \"operation_number\": operation_number,", + " }", + "", + " if (writeColon):", + " outF.write(\", \")", + "", + " writeColon = True", + " json.dump(res, outF, indent=2)", + "", + " outF.write(\"\"\"", + " ] }\"\"\")", + " outF.flush()", + "", + " else:", + " logger.error(\"Could not find atoms in %s\" % self.name)", + "", + "", + " filename = os.path.abspath(", + " os.path.normpath(", + " os.path.join(", + " path, '%s_%d_%d_op%d%s' %", + " (self.name, gIndexRun, gIndexDesc, operation_number, filename_suffix))))", + "", + " filename_list.append(filename)", + "", + " else:", + " raise Exception(\"Please specify a valid file format.\")", + "", + " return filename_list" + ], + "hidden": true + }, + "output": { + "state": {}, + "selectedType": "BeakerDisplay", + "pluginName": "IPython", + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 5295, + "height": 88 + }, + "evaluatorReader": true, + "lineCount": 1385, + "tags": "cell_soap_run", + "initialization": true + }, { "id": "codeQ4vsu9", "type": "code", @@ -2893,8 +4288,8 @@ "state": {}, "selectedType": "Results", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 641, + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 253, "dataresult": { "name": "Fe_query", "timestamp": 1516012342, @@ -12912,36 +14307,196 @@ "path": "data/2018-01-15 103222 Fe_query.json", "data": {} }, - "height": 91 + "height": 177 }, "evaluatorReader": true, "lineCount": 55, - "initialization": true, "tags": "cell_soap_run" }, { - "id": "code5mRsI5", + "id": "codeIfeJrQ", "type": "code", "evaluator": "IPython", "input": { "body": [ - "query_name = options['query']['query_name']", - "nmd_query_saved = nomad_query.fetch(name_or_index=query_name, resolve=False)", + "def _get_structures(", + " json_list=None,", + " frame_list=None,", + " file_format=None,", + " png_path=None,", + " geo_path=None,", + " desc_path=None,", + " tmp_folder=None,", + " cell_type=None,", + " operations_on_structure=None,", + " op_list=None,", + " descriptor=None,", + " atoms_scaling=None):", + " \"\"\" Obtain the NOMADstructure from each json file in the json_list;", + " write geometry files and figures to disk that will be later used to", + " plot the results in the Viewer.", "", - "MAX_NB_RES = int(options['query']['max_nb_res']) #for faster computation", - "MAX_CATEGORIES = 5 #for compatibility with the Viewer", + " Parameters", + " ----------", "", - "# resolve only a limited number of URIs", - "max_nb_uris = int(options['query']['max_nb_res'])*MAX_CATEGORIES", + " json_list : list", + " List with the absolute paths to the json files", "", - "if nmd_query_saved['uri'] == 0 :", - " logger.error(\"Your query did not yield any results. Please use another query for the analysis\")", - " sys.exit()", + " frame_list : list or list of list, optional", + " For each json file, specifies with frames to consider in the descriptor", + " calculation. If multiple json files are present, it is a list of lists.", "", - "if len(nmd_query_saved['uri']) > max_nb_uris:", - " # fix random seeds to have consistent runs", - " random.seed(42)", - " nmd_uri_sampled = random.sample(nmd_query_saved['uri'], max_nb_uris)", + " file_format : text, optional, default 'NOMAD'", + " Specify what is the format of the file to read.", + " Possible values: 'NOMAD' and 'rdf' (rdf is deprecated).", + "", + " png_path : text, optional, default tmp_folder", + " Path to the folder where the png file for each structure are written.", + "", + " geo_path : text, optional, default tmp_folder", + " Path to the folder where the png file for each structure are written.", + "", + " tmp_folder : text", + " Temporary folder.", + "", + " descriptor: object Descriptor", + "", + "", + " Returns", + " ----------", + "", + " structure_list: list, shape (len(json_list), )", + " List of NOMADstuctures. Each element in the list is an instance of the", + " class NOMADstructure; such instance can contain multiple frames", + " (see nomad_structures.py for more detail on the class NOMADstructure).", + "", + " \"\"\"", + "", + " structure_list = []", + "", + " if tmp_folder is None:", + " tmp_folder = './tmp'", + "", + " if geo_path is None:", + " geo_path = tmp_folder", + "", + " if png_path is None:", + " png_path = tmp_folder", + " ", + " if desc_path is None:", + " desc_path = tmp_folder", + "", + " logger.info(\"Generating figures and geometry files.\")", + "", + " # get unique list of json files ", + " # this is important when operations are applied to the json files", + " # this does not conserve the order", + " #json_list = list(set(json_list))", + " # NOTE: we should do something more robust", + " new_json_list = []", + " for item in json_list:", + " if item not in new_json_list:", + " new_json_list.append(item)", + " ", + " json_list = new_json_list", + " ", + " for idx, json_file in enumerate(json_list):", + " # read structure", + " if file_format == 'rdf' or file_format == 'NOMAD':", + " try:", + " # frame_list is a list of lists -> extract the list referring", + " # to each JSON file", + " frame_list_json = frame_list[idx]", + " except:", + " # frame_list is a list -> the frame_list_json is the list", + " # itself", + " frame_list_json = frame_list", + "", + " # make the first \"pristine\" structure", + " structure = NOMADStructure(", + " in_file=json_file,", + " frame_list=frame_list_json,", + " file_format=file_format,", + " cell_type=cell_type,", + " descriptor=descriptor)", + " ", + " try:", + " structure_op = _apply_operations(structure, operations_on_structure)", + " except:", + " # do not apply operation", + " # this is a hack to visualize non-periodic structures ", + " # this is very dangerous, should be changed asap", + " structure_op = _apply_operations(structure, operations_on_structure=None)", + "", + " ", + " for op_id, structure in enumerate(structure_op):", + " # write coordinates of structure", + " structure.write_geometry(path=geo_path, operation_number=op_list[op_id])", + " #structure.write_png(path=png_path, replicas=(3, 3, 3), ", + " structure.write_png(path=png_path, replicas=(1, 1, 1), ", + " rotation=True, operation_number=op_list[op_id])", + " ", + " # calculate descriptor", + " if descriptor is not None:", + " descriptor.write(", + " structure, path=desc_path, ", + " operation_number=op_id,", + " atoms_scaling=atoms_scaling)", + " ", + " ", + " else:", + " raise Exception(\"Please specify a valid file format. Possible file formats are 'NOMAD' or 'rdf'.\")", + "", + "", + "", + " structure_list.append(structure_op)", + "", + " if idx % (int(len(json_list) / 10) + 1) == 0:", + " logger.info(", + " \"Generating figures and geometries: file {0}/{1}\".format(idx + 1, len(json_list)))", + "", + " logger.info(\"Generating figures and geometry files: done.\")", + "", + " return structure_list" + ], + "hidden": true + }, + "output": { + "state": {}, + "selectedType": "Hidden", + "pluginName": "IPython", + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 511, + "height": 88 + }, + "evaluatorReader": true, + "tags": "cell_soap_run", + "lineCount": 139, + "initialization": true + }, + { + "id": "code5mRsI5", + "type": "code", + "evaluator": "IPython", + "input": { + "body": [ + "query_name = options['query']['query_name']", + "nmd_query_saved = nomad_query.fetch(name_or_index=query_name, resolve=False)", + "", + "MAX_NB_RES = int(options['query']['max_nb_res']) #for faster computation", + "MAX_CATEGORIES = 5 #for compatibility with the Viewer", + "", + "# resolve only a limited number of URIs", + "max_nb_uris = int(options['query']['max_nb_res'])*MAX_CATEGORIES", + "", + "if nmd_query_saved['uri'] == 0 :", + " logger.error(\"Your query did not yield any results. Please use another query for the analysis\")", + " sys.exit()", + "", + "if len(nmd_query_saved['uri']) > max_nb_uris:", + " # fix random seeds to have consistent runs", + " random.seed(42)", + " nmd_uri_sampled = random.sample(nmd_query_saved['uri'], max_nb_uris)", "else:", " nmd_uri_sampled = nmd_query_saved['uri']" ], @@ -12951,8 +14506,8 @@ "state": {}, "selectedType": "Hidden", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 296, + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 536, "height": 88 }, "evaluatorReader": true, @@ -13001,7 +14556,7 @@ " # nomad json files are in SU ", " \"atom_positions\": map(lambda x: [x.x*1.0E-10,x.y*1.0E-10,x.z*1.0E-10], atoms)", " }", - "", + " ", " if atoms.pbc.all():", " # periodic structure", " res['simulation_cell'] = (atoms.get_cell()*1.0E-10).tolist()", @@ -13024,8 +14579,8 @@ "state": {}, "selectedType": "Hidden", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 322, + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 302, "height": 88 }, "evaluatorReader": true, @@ -13094,7 +14649,7 @@ " if section['section_name'] == 'section_system':", " atom_positions = np.array(nmd_dict['atom_positions']['flatData']).reshape(nmd_dict['atom_positions']['shape'])*1.0E+10", " periodicity = np.array(nmd_dict['configuration_periodic_dimensions'][0]['flatData'], dtype=bool)", - " ", + " ", " if required_keys == section['required_keys_atom_species']:", " atom_species = np.array(nmd_dict['atom_species'])", " elif required_keys == section['required_keys_atom_labels']:", @@ -13104,16 +14659,16 @@ " ", " # read cell only if periodicity is all True ", " # the Gaussian parser for non-periodic systems still the cell (0., 0., 0.) even if there is no cell", - " if np.all(periodicity): ", + " if np.all(periodicity): ", " try:", " simulation_cell = np.array(nmd_dict['simulation_cell']['flatData']).reshape(nmd_dict['simulation_cell']['shape'])*1.0E+10", " except:", " simulation_cell = None", " else:", - " logger.debug(\"Calculation {} is not periodic over 3-dimensions.\".format(nmd))", - " ", + " logger.debug(\"Calculation {} is not periodic over three dimensions.\".format(nmd))", + " ", " # create ASE object", - " if simulation_cell is not None:", + " if np.all(periodicity): ", " atoms = ase.Atoms(", " symbols=atom_species, positions=atom_positions,", " cell=simulation_cell, pbc=True)", @@ -13121,7 +14676,7 @@ " # calculate spacegroup on-the-fly", " # use spacegroup as target for crystals", " try:", - " spgroup_nb = SpacegroupAnalyzer(AseAtomsAdaptor.get_structure(atoms), symprec=0.001, angle_tolerance=1.).get_space_group_number()", + " spgroup_nb = SpacegroupAnalyzer(AseAtomsAdaptor.get_structure(atoms), symprec=0.001).get_space_group_number()", " except:", " spgroup_nb = None", " ", @@ -13131,14 +14686,14 @@ " else:", " atoms = ase.Atoms(", " symbols=atom_species, positions=atom_positions,", - " cell=None, pbc=False)", + " cell=simulation_cell, pbc=False)", " ", " # calculate pointgroup on-the-fly", " # use pointgroup as target for molecules", - " try:", - " point_group_symbol = SpacegroupAnalyzer(AseAtomsAdaptor.get_structure(atoms), symprec=0.001, angle_tolerance=1.).get_point_group_symbol()", - " except:", - " point_group_symbol = None", + " #try:", + " point_group_symbol = SpacegroupAnalyzer(AseAtomsAdaptor.get_structure(atoms), symprec=0.001).get_point_group_symbol()", + " #except:", + " # point_group_symbol = None", " ", " atoms.info['point_group_symbol'] = point_group_symbol", " atoms.info['target'] = point_group_symbol", @@ -13179,9 +14734,9 @@ "state": {}, "selectedType": "Results", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 2035, - "height": 88 + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 7779, + "height": 1672 }, "evaluatorReader": true, "lineCount": 134, @@ -13269,8 +14824,8 @@ "state": {}, "selectedType": "Hidden", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 301, + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 309, "height": 88 }, "evaluatorReader": true, @@ -13312,9 +14867,9 @@ "state": {}, "selectedType": "Results", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 224, - "height": 88 + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 201, + "height": 62 }, "evaluatorReader": true, "lineCount": 20, @@ -13366,8 +14921,8 @@ "state": {}, "selectedType": "Hidden", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 317, + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 306, "height": 88 }, "evaluatorReader": true, @@ -13438,615 +14993,2011 @@ "state": {}, "selectedType": "Results", "pluginName": "IPython", - "shellId": 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"type": "out", - "value": "[Kernel] 3 3 \n" + "value": "[Kernel] 89 89 \n" + }, + { + "type": "out", + "value": "[Kernel] 89 96 \n" + }, + { + "type": "out", + "value": "[Kernel] 89 106 \n" + }, + { + "type": "out", + "value": "[Kernel] 89 118 \n" + }, + { + "type": "out", + "value": "[Kernel] 89 120 \n" + }, + { + "type": "out", + "value": "[Kernel] 89 121 \n" + }, + { + "type": "out", + "value": "[Kernel] 96 96 \n" + }, + { + "type": "out", + "value": "[Kernel] 96 106 \n" + }, + { + "type": "out", + "value": "[Kernel] 96 118 \n" + }, + { + "type": "out", + "value": "[Kernel] 96 120 \n" + }, + { + "type": "out", + "value": "[Kernel] 96 121 \n" + }, + { + "type": "out", + "value": "[Kernel] 106 106 \n" + }, + { + "type": "out", + "value": "[Kernel] 106 118 \n" + }, + { + "type": "out", + "value": "[Kernel] 106 120 \n" + }, + { + "type": "out", + "value": "[Kernel] 106 121 \n" + }, + { + "type": "out", + "value": "[Kernel] 118 118 \n" + }, + { + "type": "out", + "value": "[Kernel] 118 120 \n" + }, + { + "type": "out", + "value": "[Kernel] 118 121 \n" + }, + { + "type": "out", + "value": "[Kernel] 120 120 \n" + }, + { + "type": "out", + "value": "[Kernel] 120 121 \n" + }, + { + "type": "out", + "value": "[Kernel] 121 121 \n" } ] }, @@ -15681,8 +18632,8 @@ "state": {}, "selectedType": "Hidden", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 3606, + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 3870, "height": 88 }, "evaluatorReader": true, @@ -15872,8 +18823,8 @@ "state": {}, "selectedType": "Hidden", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 368, + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 370, "height": 88 }, "evaluatorReader": true, @@ -15950,15 +18901,16 @@ "", "# remote tmp_json_folder created", "shutil.rmtree(tmp_json_folder)" - ] + ], + "hidden": true }, "output": { "state": {}, "selectedType": "Results", "pluginName": "IPython", - "shellId": "32B7F85D85DA4B05AC8ABA4FA6E22968", - "elapsedTime": 1730, - "height": 88 + "shellId": "2ED595F8DAE142AD8F34EA76B35AF4BA", + "elapsedTime": 5296, + "height": 185 }, "evaluatorReader": true, "lineCount": 64, @@ -15980,7 +18932,7 @@ "state": {}, "selectedType": "BeakerDisplay", "pluginName": "JavaScript", - "elapsedTime": 20, + "elapsedTime": 14, "height": 88 }, "evaluatorReader": true, @@ -16021,7 +18973,7 @@ "namespace": { "options": { "query": { - "query_name": "", + "query_name": "VASP", "max_nb_res": "25" }, "run": { @@ -16131,7 +19083,7 @@ } } }, - "viewer_result": "462b47d34c41e56d", + "viewer_result": "4a842900a713ed5b", "last_query_name": "Crystal-C" }, "locked": true -- GitLab