|
| 1 | +import json |
| 2 | +import numpy as np |
| 3 | +import openmc |
| 4 | + |
| 5 | +class CompactJSONEncoder(json.JSONEncoder): |
| 6 | + """A JSON Encoder that puts arrays of primitives on a single line.""" |
| 7 | + |
| 8 | + def __init__(self, *args, **kwargs): |
| 9 | + # Default to 2-space indentation if not specified |
| 10 | + if kwargs.get("indent") is None: |
| 11 | + kwargs["indent"] = 2 |
| 12 | + super().__init__(*args, **kwargs) |
| 13 | + self.indentation_level = 0 |
| 14 | + |
| 15 | + def default(self, o): |
| 16 | + """Handle NumPy types""" |
| 17 | + if isinstance(o, np.ndarray): |
| 18 | + return o.tolist() |
| 19 | + if isinstance(o, np.integer): |
| 20 | + return int(o) |
| 21 | + if isinstance(o, np.floating): |
| 22 | + return float(o) |
| 23 | + return json.JSONEncoder.default(self, o) |
| 24 | + |
| 25 | + def encode(self, o): |
| 26 | + """Encode JSON objects with special handling for arrays of primitives.""" |
| 27 | + if isinstance(o, (list, tuple)): |
| 28 | + # Put arrays of primitives on a single line |
| 29 | + if all(isinstance(x, (int, float, bool, str, type(None))) for x in o): |
| 30 | + return "[" + ", ".join(json.dumps(el) for el in o) + "]" |
| 31 | + # For other containers, use standard formatting |
| 32 | + return self._encode_container(o, "[", "]") |
| 33 | + if isinstance(o, dict): |
| 34 | + if not o: |
| 35 | + return "{}" |
| 36 | + # Ensure keys are strings |
| 37 | + o = {str(k) if k is not None else "null": v for k, v in o.items()} |
| 38 | + if self.sort_keys: |
| 39 | + o = dict(sorted(o.items(), key=lambda x: x[0])) |
| 40 | + # Format dictionary |
| 41 | + return self._encode_container(o, "{", "}") |
| 42 | + # For primitive types, use standard JSON encoding |
| 43 | + return json.dumps( |
| 44 | + o, |
| 45 | + skipkeys=self.skipkeys, |
| 46 | + ensure_ascii=self.ensure_ascii, |
| 47 | + check_circular=self.check_circular, |
| 48 | + allow_nan=self.allow_nan, |
| 49 | + sort_keys=self.sort_keys, |
| 50 | + separators=(self.item_separator, self.key_separator), |
| 51 | + default=self.default, |
| 52 | + ) |
| 53 | + |
| 54 | + def _encode_container(self, container, open_char, close_char): |
| 55 | + """Encode a container with proper indentation.""" |
| 56 | + is_dict = isinstance(container, dict) |
| 57 | + |
| 58 | + # Handle very small containers on single line (dicts with 1 item or less) |
| 59 | + if is_dict and len(container) <= 1: |
| 60 | + if not container: |
| 61 | + return "{}" |
| 62 | + key, value = next(iter(container.items())) |
| 63 | + return f"{{ {self.encode(key)}: {self.encode(value)} }}" |
| 64 | + |
| 65 | + # Format container across multiple lines |
| 66 | + self.indentation_level += 1 |
| 67 | + if is_dict: |
| 68 | + items = [f"{self.indent_str}{self.encode(k)}: {self.encode(v)}" for k, v in container.items()] |
| 69 | + else: |
| 70 | + items = [f"{self.indent_str}{self.encode(el)}" for el in container] |
| 71 | + self.indentation_level -= 1 |
| 72 | + |
| 73 | + return f"{open_char}\n" + ",\n".join(items) + f"\n{self.indent_str}{close_char}" |
| 74 | + |
| 75 | + def iterencode(self, data, **kwargs): |
| 76 | + """Required to also work with `json.dump`.""" |
| 77 | + return self.encode(data) |
| 78 | + |
| 79 | + @property |
| 80 | + def indent_str(self) -> str: |
| 81 | + """Get the indentation string for the current level.""" |
| 82 | + if isinstance(self.indent, int): |
| 83 | + return " " * (self.indentation_level * self.indent) |
| 84 | + elif isinstance(self.indent, str): |
| 85 | + return self.indentation_level * self.indent |
| 86 | + else: |
| 87 | + return "" |
| 88 | + |
| 89 | + |
| 90 | +def extract_cross_section_data(h5_filename, json_filename): |
| 91 | + result = {} |
| 92 | + |
| 93 | + isotope_object = openmc.data.IncidentNeutron.from_hdf5(h5_filename) |
| 94 | + result['atomic_number'] = isotope_object.atomic_number |
| 95 | + result['atomic_symbol'] = isotope_object.atomic_symbol |
| 96 | + result['atomic_weight_ratio'] = isotope_object.atomic_weight_ratio |
| 97 | + result['mass_number'] = isotope_object.mass_number |
| 98 | + result['metastable'] = isotope_object.metastable |
| 99 | + result['nuclide'] = isotope_object.name |
| 100 | + result['temperatures'] = isotope_object.temperatures |
| 101 | + |
| 102 | + result['reactions'] = {} |
| 103 | + |
| 104 | + # Collect all unique temperatures first |
| 105 | + all_temperatures = set() |
| 106 | + for reaction in isotope_object.reactions.values(): |
| 107 | + all_temperatures.update(reaction.xs.keys()) |
| 108 | + |
| 109 | + # Initialize the nested structure once |
| 110 | + for temperature in all_temperatures: |
| 111 | + result['reactions'][temperature] = {} |
| 112 | + |
| 113 | + result['energy'] = {} |
| 114 | + for temperature, energy in isotope_object.energy.items(): |
| 115 | + result['energy'][temperature] = energy |
| 116 | + |
| 117 | + for reaction_mt, reaction in isotope_object.reactions.items(): |
| 118 | + temperatures_and_tabulars=reaction.xs |
| 119 | + |
| 120 | + for temperature, tabular in temperatures_and_tabulars.items(): |
| 121 | + reaction_at_temperature_dict = {} |
| 122 | + |
| 123 | + reaction_at_temperature_dict['interpolation'] = tabular.interpolation |
| 124 | + reaction_at_temperature_dict['threshold_idx'] = tabular._threshold_idx |
| 125 | + reaction_at_temperature_dict['xs'] = tabular.x |
| 126 | + |
| 127 | + result['reactions'][temperature][reaction_mt] = reaction_at_temperature_dict |
| 128 | + |
| 129 | + # print(f"Reaction MT: {reaction_mt}, Temperature: {temperature}, Interpolation: {tabular.interpolation}, Threshold Index: {tabular._threshold_idx}, len XS: {len(tabular.x)}") |
| 130 | + |
| 131 | + with open(json_filename, 'w') as f: |
| 132 | + json.dump(result, f, cls=CompactJSONEncoder, indent=2) |
| 133 | + |
| 134 | + return result |
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