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mr_data_interface.py
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mr_data_interface.py
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"""MRData Interface."""
import numpy as np
import torch
class MRData():
"""Basic MR Data Class."""
def __init__(self) -> None:
self._header: dict = {}
self._mask: torch.Tensor | None = None
@property
def header(self) -> dict:
"""Header getter function.
Returns
-------
Header dictionary
"""
return self._header
@header.setter
def header(self, value: dict):
"""Setter for header.
Parameters
----------
value
dictionary
Returns
-------
None
"""
self._header = value
@property
def mask(self) -> torch.Tensor | None:
"""Mask getter function.
Returns
-------
Mask tensor
"""
return self._mask
@mask.setter
def mask(self, value: torch.Tensor):
"""Setter for mask.
Parameters
----------
value
torch.Tensor
Returns
-------
None
"""
self._mask = value
class ImageData(MRData):
"""Image Data Class."""
def __init__(self) -> None:
super().__init__()
self._data: torch.Tensor | None = None
@property
def data(self) -> torch.Tensor | None:
"""Getter for data.
Returns
-------
torch.Tensor
"""
return self._data
@data.setter
def data(self, value: torch.Tensor):
"""Setter for data.
Parameters
----------
value
torch.Tensor
Returns
-------
None
"""
self._data = value
@property
def numpy(self) -> np.ndarray | None:
"""Get the data as numpy array.
The function forces the conversion to cpu and detaches
from autograd.
Returns
-------
numpy nd array or None
"""
if self._data is None:
return None
return self._data.numpy(force=True)
@property
def shape(self) -> tuple | None:
"""Getter for shape of data.
Returns
-------
Shape of _data tensor or None.
"""
if self._data is None:
return None
return self._data.shape
class QMRIData(MRData):
"""QMRI Data Class."""
def __init__(self) -> None:
super().__init__()
self._t1: torch.Tensor | None = None
self._rho: torch.Tensor | None = None
# To be added in the future
# self._t2: torch.Tensor[torch.float] | None = None
# self._db0: torch.Tensor[torch.float] | None = None
@property
def t1(self) -> torch.Tensor | None:
"""Getter of T1 map.
Returns
-------
T1 map tensor
"""
return self._t1
@t1.setter
def t1(self, value: torch.Tensor) -> None:
"""Setter for t1.
Parameters
----------
var
T1 map tensor
"""
self._t1 = value
@property
def rho(self) -> torch.Tensor | None:
"""Getter of rho.
Returns
-------
rho tensor
"""
return self._rho
@rho.setter
def rho(self, value: torch.Tensor) -> None:
"""Setter of rho.
Returns
-------
None
"""
self._rho = value