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import ast
from enum import Enum
from pathlib import Path
from typing import IO
from zipfile import ZipFile
import numexpr as ne
import numpy
import numpy as np
PYTHON_ENDIANNESS = 'big'
NUMPY_FLOAT_DTYPE = ">f8"
class SpecialLogFileType(Enum):
IDA_DATA_IDENTIFIER = "IDAData logfile"
ODE_DATA_IDENTIFIER = "ODEData logfile"
NETCDF_DATA_IDENTIFIER = "NetCDFData logfile"
MOVINGBOUNDARY_DATA_IDENTIFIER = "MBSData"
COMSOLE_DATA_IDENTIFIER = "COMSOL"
@staticmethod
def from_string(s: str):
for special_log_file_type in SpecialLogFileType:
if s == special_log_file_type.value:
return special_log_file_type
return None
class DomainType(Enum):
POSTPROCESSING = "PostProcessing"
UNKNOWN = "Unknown"
VOLUME = "Volume"
MEMBRANE = "Membrane"
CONTOUR = "Contour"
NONSPATIAL = "Nonspatial"
POINT = "Point"
class VariableType(Enum):
UNKNOWN = 0
VOLUME = 1
MEMBRANE = 2
CONTOUR = 3
VOLUME_REGION = 4
MEMBRANE_REGION = 5
CONTOUR_REGION = 6
NONSPATIAL = 7
VOLUME_PARTICLE = 8
MEMBRANE_PARTICLE = 9
POINT_VARIABLE = 10
POSTPROCESSING = 999
@staticmethod
def from_string(s: str):
switcher = {
"Unknown": VariableType.UNKNOWN,
"Volume_VariableType": VariableType.VOLUME,
"Membrane_VariableType": VariableType.MEMBRANE,
"Contour_VariableType": VariableType.CONTOUR,
"Volume_Region_VariableType": VariableType.VOLUME_REGION,
"Membrane_Region_VariableType": VariableType.MEMBRANE_REGION,
"Contour_Region_VariableType": VariableType.CONTOUR_REGION,
"Nonspatial_VariableType": VariableType.NONSPATIAL,
"Volume_Particle_VariableType": VariableType.VOLUME_PARTICLE,
"Membrane_Particle_VariableType": VariableType.MEMBRANE_PARTICLE,
"Point_Variable_VariableType": VariableType.POINT_VARIABLE,
"PostProcessing_VariableType": VariableType.POSTPROCESSING
}
return switcher.get(s, VariableType.UNKNOWN)
class DataFileHeader:
magic_string: str
version_string: str
num_blocks: int
first_block_offset: int
sizeX: int
sizeY: int
sizeZ: int
def read(self, f: IO[bytes]) -> int:
read_count = 0
self.magic_string = f.read(16).decode('utf-8').split('\x00')[0]
read_count += 16
self.version_string = f.read(8).decode('utf-8').split('\x00')[0]
read_count += 8
self.num_blocks = int.from_bytes(f.read(4), byteorder=PYTHON_ENDIANNESS)
read_count += 4
self.first_block_offset = int.from_bytes(f.read(4), byteorder=PYTHON_ENDIANNESS)
read_count += 4
self.sizeX = int.from_bytes(f.read(4), byteorder=PYTHON_ENDIANNESS)
read_count += 4
self.sizeY = int.from_bytes(f.read(4), byteorder=PYTHON_ENDIANNESS)
read_count += 4
self.sizeZ = int.from_bytes(f.read(4), byteorder=PYTHON_ENDIANNESS)
read_count += 4
return read_count
class VariableInfo:
var_name: str
variable_type: VariableType
class DataBlockHeader:
var_name: VariableInfo
variable_type: VariableType
size: int
data_offset: int
def read(self, f: IO[bytes]) -> int:
read_count = 0
self.var_name: str = f.read(124).decode('utf-8').split('\x00')[0]
read_count += 124
self.variable_type = VariableType(int.from_bytes(f.read(4), byteorder=PYTHON_ENDIANNESS))
read_count += 4
self.size = int.from_bytes(f.read(4), byteorder=PYTHON_ENDIANNESS)
read_count += 4
self.data_offset = int.from_bytes(f.read(4), byteorder=PYTHON_ENDIANNESS)
read_count += 4
return read_count
class DataZipFileMetadata:
zip_file: Path
zip_entry: str
file_header: DataFileHeader
data_blocks: list[DataBlockHeader]
# constructor
def __init__(self, zip_file: Path, zip_entry: str) -> None:
self.zip_file = zip_file
self.zip_entry = zip_entry
def read(self) -> None:
with ZipFile(self.zip_file, 'r') as zip:
with zip.open(self.zip_entry) as f:
self.file_header = DataFileHeader()
self.file_header.read(f)
blocks = []
for _ in range(self.file_header.num_blocks):
data_block = DataBlockHeader()
data_block.read(f)
blocks.append(data_block)
self.data_blocks = blocks
def get_data_block_header(self, variable) -> DataBlockHeader:
for db in self.data_blocks:
if db.var_name == variable:
return db
raise ValueError(f"Variable {variable} not found in zip entry {self.zip_entry}")
class PdeDataSet:
base_dir: Path
log_filename: str
data_filenames: list[str]
zip_filenames: list[str]
data_times: list[float]
data_zip_file_metadata: dict[float, DataZipFileMetadata]
def __init__(self, base_dir: Path, log_filename: str) -> None:
self.base_dir = base_dir
self.log_filename = log_filename
self.data_filenames = []
self.zip_filenames = []
self.data_times = []
self.data_zip_file_metadata = {}
def read(self) -> None:
log_file: Path = self.base_dir / self.log_filename
with log_file.open('r') as f:
first_line = True
for line in f:
if first_line:
# if line starts with a string from SpecialLogFileType, then it is not a standard PDE log file
if SpecialLogFileType.from_string(line):
special_log_file_type = SpecialLogFileType.from_string(line)
raise NotImplementedError(f"Special log file type {special_log_file_type} not implemented")
first_line = False
_iteration, filename, zip_filename, time_str = line.split()
self.data_filenames.append(filename)
self.zip_filenames.append(zip_filename)
self.data_times.append(float(time_str))
def times(self) -> list[float]:
return self.data_times
def time_index(self, time: float) -> int:
return self.data_times.index(time)
def first_data_zip_file_metadata(self) -> DataZipFileMetadata:
first_zip_entry = self.data_zip_file_metadata.get(0.0)
if first_zip_entry is None:
first_zip_entry = DataZipFileMetadata(self.base_dir / self.zip_filenames[0], self.data_filenames[0])
first_zip_entry.read()
return first_zip_entry
def variables_block_headers(self) -> list[DataBlockHeader]:
first_zip_entry = self.first_data_zip_file_metadata()
if first_zip_entry is None:
return []
return [db for db in first_zip_entry.data_blocks]
def _get_data_zip_file_metadata(self, time: float) -> DataZipFileMetadata:
zip_entry = self.data_zip_file_metadata.get(time)
if zip_entry is None:
time_index = self.time_index(time)
zip_file_path = self.base_dir / self.zip_filenames[time_index]
zip_entry = DataZipFileMetadata(zip_file_path, self.data_filenames[time_index])
zip_entry.read()
self.data_zip_file_metadata[time] = zip_entry
return zip_entry
def get_data(self, variable: str, time: float) -> numpy.ndarray:
zip_file_entry: DataZipFileMetadata = self._get_data_zip_file_metadata(time)
data_block_header: DataBlockHeader = zip_file_entry.get_data_block_header(variable)
with (ZipFile(zip_file_entry.zip_file, 'r') as zip):
with zip.open(zip_file_entry.zip_entry, mode='r') as f:
f.seek(data_block_header.data_offset)
buffer = bytearray(0)
bytes_left_to_read = data_block_header.size * 8
while bytes_left_to_read > 0:
bytes_read = f.read(bytes_left_to_read)
buffer.extend(bytes_read)
bytes_left_to_read -= len(bytes_read)
array = np.frombuffer(buffer, dtype=NUMPY_FLOAT_DTYPE)
return array
class NamedFunction:
name: str
vcell_expression: str
python_expression: str
variables: list[str]
variable_type: VariableType
def __init__(self, name: str, vcell_expression: str, variable_type: VariableType) -> None:
self.name = name
self.vcell_expression = vcell_expression
self.python_expression = vcell_expression.replace("^", "**").lstrip(" ").rstrip(" ")
self.variable_type = variable_type
# Parse the python expression into an AST and extract all Name nodes (which represent variables)
tree = ast.parse(self.python_expression)
self.variables = [node.id for node in ast.walk(tree) if isinstance(node, ast.Name)]
def evaluate(self, variable_bindings: dict[str, np.ndarray]) -> np.ndarray:
ne.set_num_threads(1)
expression = self.python_expression
return ne.evaluate(expression, local_dict=variable_bindings)
def __str__(self):
return f"NamedFunction(name={self.name}, vcell_expression={self.vcell_expression}, python_expression={self.vcell_expression}, variable_type={self.variable_type}, variables={self.variables}"
class DataFunctions:
function_file: Path
named_functions: list[NamedFunction]
def __init__(self, function_file: Path) -> None:
self.function_file = function_file
self.named_functions = []
def read(self) -> None:
with self.function_file.open('r') as f:
# skip lines beginning with # and blank lines
for line in f:
if line.startswith('#') or line.isspace():
continue
# read each named function from one line
# example line: "cytosol::J_r0; (RanC_cyt - (1000.0 * C_cyt * Ran_cyt)); ; Volume_VariableType; false"
parts = line.split(';')
name = parts[0].strip(" ")
expression = parts[1].strip(" ")
_unknown_skipped = parts[2]
variable_type = VariableType.from_string(parts[3].strip(" "))
_boolean_skipped = parts[4]
function = NamedFunction(name=name, vcell_expression=expression, variable_type=variable_type)
self.named_functions.append(function)
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