Significantly improved acquisition, waveform and image creation speed (#66)

* Significantly improved Acquisition, waveform and image creation speed, resulting in faster deserialization

* Updated version

Author: dchansen

ismrmrd/acquisition.py

@@ -6,6 +6,7 @@
 from .constants import *
 from .flags import FlagsMixin
 from .equality import EqualityMixin
+from . import decorators
 
 
 class EncodingCounters(EqualityMixin, ctypes.Structure):
@@ -58,7 +59,6 @@ class AcquisitionHeader(FlagsMixin, EqualityMixin, ctypes.Structure):
                 ("idx", EncodingCounters),
                 ("user_int", ctypes.c_int32 * USER_INTS),
                 ("user_float", ctypes.c_float * USER_FLOATS)]
-
     def __str__(self):
         retstr = ''
         for field_name, field_type in self._fields_:
@@ -70,8 +70,9 @@ def __str__(self):
         return retstr
 
 
+@decorators.expose_header_fields(AcquisitionHeader)
 class Acquisition(FlagsMixin):
-    __readonly = ('number_of_samples', 'active_channels', 'trajectory_dimensions')
+    _readonly = ('number_of_samples', 'active_channels', 'trajectory_dimensions')
 
     @staticmethod
     def deserialize_from(read_exactly):
@@ -97,7 +98,7 @@ def deserialize_from(read_exactly):
         return acquisition
 
     def serialize_into(self, write):
-        write(self.__head)
+        write(self._head)
         write(self.__traj.tobytes())
         write(self.__data.tobytes())
 
@@ -146,7 +147,7 @@ def __init__(self, head=None, data=None, trajectory=None):
         def generate_header():
             if head is None:
                 if data is None:
-                    return AcquisitionHeader()
+                    return  AcquisitionHeader()
                 else:
                     nchannels, nsamples = data.shape
                     trajectory_dimensions = trajectory.shape[1] if trajectory is not None else 0
@@ -170,55 +171,26 @@ def generate_trajectory_array(header):
             return trajectory if trajectory is not None else np.zeros(
                 shape=(header.number_of_samples, header.trajectory_dimensions), dtype=np.float32)
 
-        self.__head = generate_header()
-
-        self.__data = generate_data_array(self.__head)
-        self.__traj = generate_trajectory_array(self.__head)
-
-        for (field, _) in self.__head._fields_:
-            try:
-                g = '__get_' + field
-                s = '__set_' + field
-                setattr(Acquisition, g, self.__getter(field))
-                setattr(Acquisition, s, self.__setter(field))
-                p = property(getattr(Acquisition, g), getattr(Acquisition, s))
-                setattr(Acquisition, field, p)
-            except TypeError:
-                # e.g. if key is an `int`, skip it
-                pass
-
-    def __getter(self, name):
-        if name in self.__readonly:
-            def fn(self):
-                return copy.copy(self.__head.__getattribute__(name))
-        else:
-            def fn(self):
-                return self.__head.__getattribute__(name)
-        return fn
-
-    def __setter(self, name):
-        if name in self.__readonly:
-            def fn(self, val):
-                raise AttributeError(name + " is read-only. Use resize instead.")
-        else:
-            def fn(self, val):
-                self.__head.__setattr__(name, val)
-
-        return fn
+        self._head = generate_header()
+
+        self.__data = generate_data_array(self._head)
+        self.__traj = generate_trajectory_array(self._head)
+
+
 
     def resize(self, number_of_samples=0, active_channels=1, trajectory_dimensions=0):
         self.__data = np.resize(self.__data, (active_channels, number_of_samples))
         self.__traj = np.resize(self.__traj, (number_of_samples, trajectory_dimensions))
-        self.__head.number_of_samples = number_of_samples
-        self.__head.active_channels = active_channels
-        self.__head.trajectory_dimensions = trajectory_dimensions
+        self._head.number_of_samples = number_of_samples
+        self._head.active_channels = active_channels
+        self._head.trajectory_dimensions = trajectory_dimensions
 
     def getHead(self):
-        return copy.deepcopy(self.__head)
+        return copy.deepcopy(self._head)
 
     def setHead(self, hdr):
-        self.__head = self.__head.__class__.from_buffer_copy(hdr)
-        self.resize(self.__head.number_of_samples, self.__head.active_channels, self.__head.trajectory_dimensions)
+        self._head = self._head.__class__.from_buffer_copy(hdr)
+        self.resize(self._head.number_of_samples, self._head.active_channels, self._head.trajectory_dimensions)
 
     @property
     def data(self):
@@ -230,7 +202,7 @@ def traj(self):
 
     def __str__(self):
         retstr = ''
-        retstr += 'Header:\n %s\n' % (self.__head)
+        retstr += 'Header:\n %s\n' % (self._head)
         retstr += 'Trajectory:\n %s\n' % (self.traj)
         retstr += 'Data:\n %s\n' % (self.data)
         return retstr
@@ -240,7 +212,8 @@ def __eq__(self, other):
             return False
 
         return all([
-            self.__head == other.__head,
+            self._head == other._head,
             np.array_equal(self.__data, other.__data),
             np.array_equal(self.__traj, other.__traj)
         ])
+

ismrmrd/decorators.py

@@ -0,0 +1,42 @@
+import copy 
+
+
+class  expose_header_fields:
+    def __init__(self,header_cls) -> None:
+        self.header_cls = header_cls
+
+    def __call__(self,cls):
+        def create_getter_and_setter(field):
+            if field in cls._readonly:
+                def getter(self):
+                    return copy.copy(self._head.__getattribute__(field))
+                def setter(self,val):
+                    raise AttributeError(field+ " is read-only. Use resize instead.")
+            else:
+                def getter(self):
+                    return self._head.__getattribute__(field)
+                def setter(self, val):
+                    self._head.__setattr__(field, val)
+            
+            return getter,setter
+    
+        ignore_list = cls._ignore if hasattr(cls,"_ignore") else []
+    
+        for (field, _) in self.header_cls._fields_:
+            if field in ignore_list:
+                continue 
+            try:
+                g = '__get_' + field
+                s = '__set_' + field
+    
+                getter,setter = create_getter_and_setter(field)
+                setattr(cls, g, getter)
+                setattr(cls, s, setter)
+                p = property(getattr(cls, g), getattr(cls, s))
+                setattr(cls, field, p)
+            except TypeError:
+                # e.g. if key is an `int`, skip it
+                pass
+    
+        return cls 
+

ismrmrd/file.py

@@ -18,7 +18,7 @@ def __len__(self):
 
     def __iter__(self):
         for raw in self.data:
-            yield self.from_numpy(raw)
+                yield self.from_numpy(raw)
 
     def __getitem__(self, key):
         if isinstance(key, slice):
@@ -65,17 +65,14 @@ def __init__(self, data):
 
     @classmethod
     def from_numpy(cls, raw):
-        acquisition = Acquisition(raw['head'])
-
-        acquisition.data[:] = raw['data'].view(np.complex64).reshape(
-            (acquisition.active_channels,
-             acquisition.number_of_samples)
-        )[:]
-
-        acquisition.traj[:] = raw['traj'].reshape(
-            (acquisition.number_of_samples,
-             acquisition.trajectory_dimensions)
-        )[:]
+        acquisition = Acquisition(raw['head'],raw['data'].view(np.complex64).reshape(
+            (raw['head']['active_channels'],
+             raw['head']['number_of_samples'])
+        ),
+        raw['traj'].reshape(
+            (raw['head']['number_of_samples'],
+             raw['head']['trajectory_dimensions']
+        )))
 
         return acquisition
 
@@ -378,11 +375,14 @@ def has_acquisitions(self):
 class File(Folder):
 
     def __init__(self, filename, mode='a'):
-        self.__file = h5py.File(filename, mode)
+        self.__file = h5py.File(filename, mode,driver='stdio')
         super().__init__(self.__file)
 
     def __enter__(self):
         return self
 
     def __exit__(self, exc_type, exc_value, traceback):
         self.__file.close()
+
+    def close(self):
+        self.__file.close()

ismrmrd/image.py

@@ -12,6 +12,7 @@
 from .flags import FlagsMixin
 from .equality import EqualityMixin
 from .constants import *
+from . import decorators
 
 dtype_mapping = {
     DATATYPE_USHORT: np.dtype('uint16'),
@@ -125,9 +126,10 @@ def __repr__(self):
 
 
 # Image class
+@decorators.expose_header_fields(ImageHeader)
 class Image(FlagsMixin):
-    __readonly = ('data_type', 'matrix_size', 'channels')
-    __ignore = ('matrix_size', 'attribute_string_len')
+    _readonly = ('data_type', 'matrix_size', 'channels')
+    _ignore = ('matrix_size', 'attribute_string_len')
 
     @staticmethod
     def deserialize_from(read_exactly):
@@ -154,9 +156,9 @@ def calculate_number_of_entries(nchannels, xs, ys, zs):
     def serialize_into(self, write):
 
         attribute_bytes = self.attribute_string.encode('utf-8')
-        self.__head.attribute_string_len = len(attribute_bytes)
+        self._head.attribute_string_len = len(attribute_bytes)
 
-        write(self.__head)
+        write(self._head)
 
         write(ctypes.c_uint64(len(attribute_bytes)))
         write(attribute_bytes)
@@ -229,15 +231,15 @@ def create_consistent_header(header, data):
         if head is None:
             if data is None:
                 data = np.empty((1, 1, 1, 0), dtype=np.complex64)
-            self.__head = create_consistent_header(ImageHeader(), data)
+            self._head = create_consistent_header(ImageHeader(), data)
         else:
-            self.__head = ImageHeader.from_buffer_copy(head)
+            self._head = ImageHeader.from_buffer_copy(head)
             if data is None:
-                data = np.empty(shape=(self.__head.channels, self.__head.matrix_size[2],
-                                              self.__head.matrix_size[1], self.__head.matrix_size[0]),
-                                       dtype=get_dtype_from_data_type(self.__head.data_type))
+                data = np.empty(shape=(self._head.channels, self._head.matrix_size[2],
+                                              self._head.matrix_size[1], self._head.matrix_size[0]),
+                                       dtype=get_dtype_from_data_type(self._head.data_type))
             else:
-                self.__head = create_consistent_header(self.__head, data)
+                self._head = create_consistent_header(self._head, data)
         self.__data = data
 
         if attribute_string is not None:
@@ -249,48 +251,14 @@ def create_consistent_header(header, data):
         else:
             self.__meta = Meta()
 
-        for (field, type) in self.__head._fields_:
-            if field in self.__ignore:
-                continue
-            else:
-                try:
-                    g = '__get_' + field
-                    s = '__set_' + field
-                    setattr(Image, g, self.__getter(field))
-                    setattr(Image, s, self.__setter(field))
-                    p = property(getattr(Image, g), getattr(Image, s))
-                    setattr(Image, field, p)
-                except TypeError:
-                    # e.g. if key is an `int`, skip it
-                    pass
-
-    def __getter(self, name):
-        if name in self.__readonly:
-            def fn(self):
-                return copy.copy(self.__head.__getattribute__(name))
-        else:
-            def fn(self):
-                return self.__head.__getattribute__(name)
-        return fn
-
-    def __setter(self, name):
-        if name in self.__readonly:
-            def fn(self, val):
-                raise AttributeError(name + " is read-only.")
-        else:
-            def fn(self, val):
-                self.__head.__setattr__(name, val)
-
-        return fn
-
     def getHead(self):
-        return copy.deepcopy(self.__head)
+        return copy.deepcopy(self._head)
 
     def setHead(self, hdr):
-        self.__head = self.__head.__class__.from_buffer_copy(hdr)
-        self.setDataType(self.__head.data_type)
-        self.resize(self.__head.channels, self.__head.matrix_size[2], self.__head.matrix_size[1],
-                    self.__head.matrix_size[0])
+        self._head = self._head.__class__.from_buffer_copy(hdr)
+        self.setDataType(self._head.data_type)
+        self.resize(self._head.channels, self._head.matrix_size[2], self._head.matrix_size[1],
+                    self._head.matrix_size[0])
 
     def setDataType(self, val):
         self.__data = self.__data.astype(get_dtype_from_data_type(val))
@@ -340,18 +308,18 @@ def attribute_string_len(self):
         return len(self.attribute_string)
 
     def __str__(self):
-        return "Header:\n {}\nAttribute string:\n {}\nData:\n {}\n".format(self.__head, self.attribute_string,
+        return "Header:\n {}\nAttribute string:\n {}\nData:\n {}\n".format(self._head, self.attribute_string,
                                                                            self.__data)
 
     def __repr__(self):
-        return f"Image(head={self.__head.__repr__()},meta={self.__meta.__repr__()},data={self.__data.__repr__()})"
+        return f"Image(head={self._head.__repr__()},meta={self.__meta.__repr__()},data={self.__data.__repr__()})"
 
     def __eq__(self, other):
         if not isinstance(other, Image):
             return False
 
         return all([
-            self.__head == other.__head,
+            self._head == other._head,
             np.array_equal(self.__data, other.__data),
             np.array_equal(self.attribute_string, other.attribute_string)
         ])