Files
SystemSimulationApp/PythonModels/reporting/amesim_results.py
T

151 lines
5.2 KiB
Python

from __future__ import annotations
import re
import struct
import tarfile
from dataclasses import dataclass
from pathlib import Path
class AmesimResultsError(ValueError):
"""Raised when AMESim result files cannot be parsed consistently."""
@dataclass(frozen=True)
class AmesimVariable:
index: int
label: str
data_path: str | None
param_id: int | None
hidden: bool
@dataclass(frozen=True)
class AmesimResults:
times: tuple[float, ...]
variables: tuple[AmesimVariable, ...]
saved_variable_indices: tuple[int, ...]
series_by_data_path: dict[str, tuple[float, ...]]
final_values_by_data_path: dict[str, float]
@property
def point_count(self) -> int:
return len(self.times)
@property
def saved_variable_count(self) -> int:
return len(self.saved_variable_indices)
def series(self, data_path: str) -> tuple[float, ...]:
return self.series_by_data_path[data_path]
def final_value(self, data_path: str) -> float:
return self.final_values_by_data_path[data_path]
_DATA_PATH_RE = re.compile(r"Data_Path=(\S+)")
_PARAM_ID_RE = re.compile(r"Param_Id=(\d+)")
def load_test_mql_amesim_results(archive_path: str | Path) -> AmesimResults:
return load_amesim_results_from_archive(
archive_path=archive_path,
var_member="test_mql_.var",
results_member="test_mql_.results",
)
def load_amesim_results_from_archive(
*,
archive_path: str | Path,
var_member: str,
results_member: str,
) -> AmesimResults:
with tarfile.open(archive_path) as archive:
var_file = archive.extractfile(var_member)
results_file = archive.extractfile(results_member)
if var_file is None:
raise AmesimResultsError(f"Missing AMESim variable member: {var_member}")
if results_file is None:
raise AmesimResultsError(f"Missing AMESim results member: {results_member}")
var_lines = var_file.read().decode("latin1").splitlines()
results_data = results_file.read()
variables = tuple(_parse_variable_line(index, line) for index, line in enumerate(var_lines))
return parse_amesim_results_bytes(results_data, variables)
def parse_amesim_results_bytes(
results_data: bytes,
variables: tuple[AmesimVariable, ...],
) -> AmesimResults:
if len(results_data) < 8:
raise AmesimResultsError("AMESim results data is too small.")
point_count, encoded_saved_variable_count = struct.unpack_from("<2i", results_data, 0)
saved_variable_count = abs(encoded_saved_variable_count)
if point_count <= 0 or saved_variable_count <= 0:
raise AmesimResultsError("Invalid AMESim results header.")
mapping_offset = 8
mapping_size = saved_variable_count * 4
data_offset = mapping_offset + mapping_size
saved_variable_indices = struct.unpack_from(
f"<{saved_variable_count}i",
results_data,
mapping_offset,
)
if any(index < 0 or index >= len(variables) for index in saved_variable_indices):
raise AmesimResultsError(
"AMESim results variable mapping references unknown .var rows."
)
row_length = 1 + saved_variable_count
main_value_count = point_count * row_length
main_byte_count = main_value_count * 8
main_end = data_offset + main_byte_count
if main_end > len(results_data):
raise AmesimResultsError("AMESim results matrix is truncated.")
main_values = struct.unpack_from(f"<{main_value_count}d", results_data, data_offset)
times = tuple(main_values[row * row_length] for row in range(point_count))
series_by_data_path: dict[str, tuple[float, ...]] = {}
for column, variable_index in enumerate(saved_variable_indices, start=1):
variable = variables[variable_index]
if variable.data_path is None:
continue
series_by_data_path[variable.data_path] = tuple(
main_values[row * row_length + column]
for row in range(point_count)
)
final_values_by_data_path: dict[str, float] = {}
trailing_bytes = len(results_data) - main_end
expected_final_bytes = (1 + len(variables)) * 8
if trailing_bytes >= expected_final_bytes:
final_values = struct.unpack_from(f"<{1 + len(variables)}d", results_data, main_end)
for variable, value in zip(variables, final_values[1:]):
if variable.data_path is not None:
final_values_by_data_path[variable.data_path] = value
return AmesimResults(
times=times,
variables=variables,
saved_variable_indices=tuple(saved_variable_indices),
series_by_data_path=series_by_data_path,
final_values_by_data_path=final_values_by_data_path,
)
def _parse_variable_line(index: int, line: str) -> AmesimVariable:
data_path_match = _DATA_PATH_RE.search(line)
param_id_match = _PARAM_ID_RE.search(line)
label = line
if data_path_match is not None:
label = line[: data_path_match.start()].strip()
return AmesimVariable(
index=index,
label=label,
data_path=data_path_match.group(1) if data_path_match else None,
param_id=int(param_id_match.group(1)) if param_id_match else None,
hidden="HIDDEN" in line,
)