diff options
| -rwxr-xr-x | Wrappers/Python/ccpi/framework/framework.py | 89 |
1 files changed, 69 insertions, 20 deletions
diff --git a/Wrappers/Python/ccpi/framework/framework.py b/Wrappers/Python/ccpi/framework/framework.py index 0c43737..3707c07 100755 --- a/Wrappers/Python/ccpi/framework/framework.py +++ b/Wrappers/Python/ccpi/framework/framework.py @@ -44,6 +44,13 @@ def message(cls, msg, *args): class ImageGeometry(object): + RANDOM = 'random' + RANDOM_INT = 'random_int' + CHANNEL = 'channel' + ANGLE = 'angle' + VERTICAL = 'vertical' + HORIZONTAL_X = 'horizontal_x' + HORIZONTAL_Y = 'horizontal_y' def __init__(self, voxel_num_x=0, @@ -73,20 +80,22 @@ class ImageGeometry(object): if self.voxel_num_z>1: self.length = 4 self.shape = (self.channels, self.voxel_num_z, self.voxel_num_y, self.voxel_num_x) - dim_labels = ['channel' ,'vertical' , 'horizontal_y' , 'horizontal_x'] + dim_labels = [ImageGeometry.CHANNEL, ImageGeometry.VERTICAL, + ImageGeometry.HORIZONTAL_Y, ImageGeometry.HORIZONTAL_X] else: self.length = 3 self.shape = (self.channels, self.voxel_num_y, self.voxel_num_x) - dim_labels = ['channel' , 'horizontal_y' , 'horizontal_x'] + dim_labels = [ImageGeometry.CHANNEL, ImageGeometry.HORIZONTAL_Y, ImageGeometry.HORIZONTAL_X] else: if self.voxel_num_z>1: self.length = 3 self.shape = (self.voxel_num_z, self.voxel_num_y, self.voxel_num_x) - dim_labels = ['vertical', 'horizontal_y' , 'horizontal_x'] + dim_labels = [ImageGeometry.VERTICAL, ImageGeometry.HORIZONTAL_Y, + ImageGeometry.HORIZONTAL_X] else: self.length = 2 self.shape = (self.voxel_num_y, self.voxel_num_x) - dim_labels = ['horizontal_y' , 'horizontal_x'] + dim_labels = [ImageGeometry.HORIZONTAL_Y, ImageGeometry.HORIZONTAL_X] self.dimension_labels = dim_labels @@ -134,23 +143,49 @@ class ImageGeometry(object): repres += "voxel_size : x{0},y{1},z{2}\n".format(self.voxel_size_x, self.voxel_size_y, self.voxel_size_z) repres += "center : x{0},y{1},z{2}\n".format(self.center_x, self.center_y, self.center_z) return repres - def allocate(self, value=0, dimension_labels=None): + def allocate(self, value=0, dimension_labels=None, **kwargs): '''allocates an ImageData according to the size expressed in the instance''' out = ImageData(geometry=self) if isinstance(value, Number): if value != 0: out += value else: - if value == 'random': + if value == ImageData.RANDOM: + seed = kwargs.get('seed', None) + if seed is not None: + numpy.random.seed(seed) out.fill(numpy.random.random_sample(self.shape)) - elif value == 'random_int': - out.fill(numpy.random.randint(1, 10 + 1,size=self.shape)) + elif value == ImageData.RANDOM_INT: + seed = kwargs.get('seed', None) + if seed is not None: + numpy.random.seed(seed) + max_value = kwargs.get('max_value', 100) + out.fill(numpy.random.randint(max_value,size=self.shape)) if dimension_labels is not None: if dimension_labels != self.dimension_labels: return out.subset(dimensions=dimension_labels) return out + # The following methods return 2 members of the class, therefore I + # don't think we need to implement them. + # Additionally using __len__ is confusing as one would think this is + # an iterable. + #def __len__(self): + # '''returns the length of the geometry''' + # return self.length + #def shape(self): + # '''Returns the shape of the array of the ImageData it describes''' + # return self.shape + class AcquisitionGeometry(object): - + RANDOM = 'random' + RANDOM_INT = 'random_int' + ANGLE_UNIT = 'angle_unit' + DEGREE = 'degree' + RADIAN = 'radian' + CHANNEL = 'channel' + ANGLE = 'angle' + VERTICAL = 'vertical' + HORIZONTAL = 'horizontal' def __init__(self, geom_type, dimension, @@ -162,7 +197,7 @@ class AcquisitionGeometry(object): dist_source_center=None, dist_center_detector=None, channels=1, - angle_unit='degree', + **kwargs ): """ General inputs for standard type projection geometries @@ -204,21 +239,26 @@ class AcquisitionGeometry(object): self.pixel_size_v = pixel_size_v self.channels = channels - + self.angle_unit=kwargs.get(AcquisitionGeometry.ANGLE_UNIT, + AcquisitionGeometry.DEGREE) if channels > 1: if pixel_num_v > 1: shape = (channels, num_of_angles , pixel_num_v, pixel_num_h) - dim_labels = ['channel' , 'angle' , 'vertical' , 'horizontal'] + dim_labels = [AcquisitionGeometry.CHANNEL , + AcquisitionGeometry.ANGLE , AcquisitionGeometry.VERTICAL , + AcquisitionGeometry.HORIZONTAL] else: shape = (channels , num_of_angles, pixel_num_h) - dim_labels = ['channel' , 'angle' , 'horizontal'] + dim_labels = [AcquisitionGeometry.CHANNEL , + AcquisitionGeometry.ANGLE, AcquisitionGeometry.HORIZONTAL] else: if pixel_num_v > 1: shape = (num_of_angles, pixel_num_v, pixel_num_h) - dim_labels = ['angle' , 'vertical' , 'horizontal'] + dim_labels = [AcquisitionGeometry.ANGLE , AcquisitionGeometry.VERTICAL , + AcquisitionGeometry.HORIZONTAL] else: shape = (num_of_angles, pixel_num_h) - dim_labels = ['angle' , 'horizontal'] + dim_labels = [AcquisitionGeometry.ANGLE, AcquisitionGeometry.HORIZONTAL] self.shape = shape self.dimension_labels = dim_labels @@ -254,10 +294,17 @@ class AcquisitionGeometry(object): if value != 0: out += value else: - if value == 'random': + if value == AcquisitionData.RANDOM: + seed = kwargs.get('seed', None) + if seed is not None: + numpy.random.seed(seed) out.fill(numpy.random.random_sample(self.shape)) - elif value == 'random_int': - out.fill(numpy.random.out.fill(numpy.random.randint(1, 10 + 1,size=self.shape))) + elif value == AcquisitionData.RANDOM_INT: + seed = kwargs.get('seed', None) + if seed is not None: + numpy.random.seed(seed) + max_value = kwargs.get('max_value', 100) + out.fill(numpy.random.randint(max_value,size=self.shape)) if dimension_labels is not None: if dimension_labels != self.dimension_labels: return out.subset(dimensions=dimension_labels) @@ -810,8 +857,8 @@ class DataContainer(object): #shape = self.shape #size = reduce(lambda x,y:x*y, shape, 1) #y = numpy.reshape(self.as_array(), (size, )) - #return numpy.dot(y, y.conjugate()) - return self.dot(self) + return self.dot(self.conjugate()) + #return self.dot(self) def norm(self): '''return the euclidean norm of the DataContainer viewed as a vector''' return numpy.sqrt(self.squared_norm()) @@ -828,6 +875,7 @@ class DataContainer(object): class ImageData(DataContainer): '''DataContainer for holding 2D or 3D DataContainer''' + def __init__(self, array = None, deep_copy=False, @@ -939,6 +987,7 @@ class ImageData(DataContainer): class AcquisitionData(DataContainer): '''DataContainer for holding 2D or 3D sinogram''' + def __init__(self, array = None, deep_copy=True, |