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Commit c2d3607a authored by Martin Genet's avatar Martin Genet
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New k-space resampling in generate_images

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__init__.py
+ 25
− 20
View file @ c2d3607a
#this file was generated by __init__.py.py #this file was generated by __init__.py.py
from compute_displacement_error import * from fedic import *
from compute_displacements import * from plot_binned_strains_vs_radius import *
from compute_quadrature_degree import * from NonlinearSolver import *
from compute_strains import * from MeshSeries import *
from generated_image_expressions_cpp import *
from plot_strains_vs_radius import *
from Energy_GeneratedImage import *
from compute_unwarped_images import * from compute_unwarped_images import *
from Problem_ImageRegistration import *
from compute_quadrature_degree import *
from Energy_Regularization import *
from compute_warped_images import * from compute_warped_images import *
from compute_warped_mesh import * from plot_strains import *
from image_expressions_cpp import *
from resample_images import *
from Energy import * from Energy import *
from Energy_Regularization import * from compute_warped_mesh import *
from Energy_WarpedImage import * from Energy_WarpedImage import *
from fedic import * from write_VTU_file import *
from fedic2 import *
from generate_images import *
from generate_undersampled_images import * from generate_undersampled_images import *
from generated_image_expressions_cpp import * from normalize_images import *
from image_expressions_cpp import * from plot_regional_strains import *
from image_expressions_py import * from image_expressions_py import *
from ImageIterator import * from ImageIterator import *
from ImageSeries import * from fedic2 import *
from MeshSeries import * from generated_grad_expressions_cpp import *
from NonlinearSolver import *
from plot_binned_strains_vs_radius import *
from plot_displacement_error import * from plot_displacement_error import *
from plot_regional_strains import *
from plot_strains import *
from plot_strains_vs_radius import *
from Problem import * from Problem import *
from Problem_ImageRegistration import * from compute_displacements import *
from write_VTU_file import * from generate_images import *
from ImageSeries import *
from compute_displacement_error import *
from project import *
from compute_strains import *
generate_images.py
+ 26
− 677
View file @ c2d3607a
...@@ -19,640 +19,8 @@ import myPythonLibrary as mypy ...@@ -19,640 +19,8 @@ import myPythonLibrary as mypy
import myVTKPythonLibrary as myvtk import myVTKPythonLibrary as myvtk
import dolfin_dic as ddic import dolfin_dic as ddic
from generate_images_Image import Image
################################################################################ from generate_images_Mapping import Mapping
#class ImagesInfo():
#def __init__(self, n_dim, L, n_voxels, n_integration, T, n_frames, data_type, images_folder, images_basename):
#assert (n_dim in (1,2,3))
#self.n_dim = n_dim
#if (type(L) == float):
#assert (L>0)
#self.L = numpy.array([L]*self.n_dim)
#elif (type(L) == int):
#assert (L>0)
#self.L = numpy.array([float(L)]*self.n_dim)
#else:
#assert (len(L) == self.n_dim)
#self.L = numpy.array(L)
#assert ((self.L>0).all())
#if (type(n_voxels) == int):
#assert (n_voxels>0)
#self.n_voxels = numpy.array([n_voxels]*self.n_dim)
#else:
#assert (len(n_voxels) == self.n_dim)
#self.n_voxels = numpy.array(n_voxels)
#assert ((self.n_voxels>0).all())
#if (type(n_integration) == int):
#assert (n_integration>0)
#self.n_integration = numpy.array([n_integration]*self.n_dim)
#else:
#assert (len(n_integration) == self.n_dim)
#self.n_integration = numpy.array(n_integration)
#assert ((self.n_integration>0).all())
#assert (T>0.)
#self.T = T
#assert (n_frames>0)
#self.n_frames = n_frames
#assert (data_type in ("int", "float", "unsigned char", "unsigned short", "unsigned int", "unsigned long", "unsigned float" "uint8", "uint16", "uint32", "uint64", "ufloat"))
#self.data_type = data_type
#self.images_folder = images_folder
#self.images_basename = images_basename
#class StructureInfo():
#def __init__(self, images, type, **kwargs):
#assert (type in ("no", "heart"))
#self["type"] = type
#if (self["type"] == "heart"):
#self.Ri = kwargs["Ri"]
#self.Re = kwargs["Re"]
#if (images.n_dim == 3):
#self.Zmin = kwargs["Zmin"] if ("Zmin" in kwargs.keys()) else 0.
#self.Zmax = kwargs["Zmax"] if ("Zmax" in kwargs.keys()) else images.L[2]
#class TextureInfo():
#def __init__(self, type, **kwargs):
#assert (type in ("no", "taggX", "taggY", "taggZ"))
#self["type"] = type
#class NoiseInfo():
#def __init__(self, type, **kwargs):
#self["type"] = type
#class DeformationInfo():
#def __init__(self, type, **kwargs):
#self["type"] = type
#class EvolutionInfo():
#def __init__(self, type, **kwargs):
#self["type"] = type
################################################################################
class Image():
def __init__(self, images, structure, texture, noise, generate_image_gradient=False):
self.L = images["L"]
# structure
if (structure["type"] == "no"):
self.I0_structure = self.I0_structure_no_wGrad if (generate_image_gradient) else self.I0_structure_no
elif (structure["type"] == "box"):
self.I0_structure = self.I0_structure_box_wGrad if (generate_image_gradient) else self.I0_structure_box
self.Xmin = structure["Xmin"]
self.Xmax = structure["Xmax"]
elif (structure["type"] == "heart"):
if (images["n_dim"] == 2):
self.I0_structure = self.I0_structure_heart_2_wGrad if (generate_image_gradient) else self.I0_structure_heart_2
self.R = float()
self.Ri = structure["Ri"]
self.Re = structure["Re"]
elif (images["n_dim"] == 3):
self.I0_structure = self.I0_structure_heart_3_wGrad if (generate_image_gradient) else self.I0_structure_heart_3
self.R = float()
self.Ri = structure["Ri"]
self.Re = structure["Re"]
self.Zmin = structure.Zmin if ("Zmin" in structure) else 0.
self.Zmax = structure.Zmax if ("Zmax" in structure) else images["L"][2]
else:
assert (0), "n_dim must be \"2\" or \"3 for \"heart\" type structure. Aborting."
else:
assert (0), "structure type must be \"no\", \"box\" or \"heart\". Aborting."
# texture
if (texture["type"] == "no"):
self.I0_texture = self.I0_texture_no_wGrad if (generate_image_gradient) else self.I0_texture_no
elif (texture["type"].startswith("tagging")):
if (images["n_dim"] == 1):
if ("-signed" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_X_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_X
else:
self.I0_texture = self.I0_texture_tagging_X_wGrad if (generate_image_gradient) else self.I0_texture_tagging_X
elif (images["n_dim"] == 2):
if ("-signed" in texture["type"]):
if ("-addComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_XY_wAdditiveCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XY_wAdditiveCombination
elif ("-diffComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_XY_wDifferentiableCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XY_wDifferentiableCombination
else:
self.I0_texture = self.I0_texture_tagging_signed_XY_wMultiplicativeCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XY_wMultiplicativeCombination
else:
if ("-addComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_XY_wAdditiveCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XY_wAdditiveCombination
elif ("-diffComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_XY_wDifferentiableCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XY_wDifferentiableCombination
else:
self.I0_texture = self.I0_texture_tagging_XY_wMultiplicativeCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XY_wMultiplicativeCombination
elif (images["n_dim"] == 3):
if ("-signed" in texture["type"]):
if ("-addComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_XYZ_wAdditiveCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XYZ_wAdditiveCombination
elif ("-diffComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_XYZ_wDifferentiableCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XYZ_wDifferentiableCombination
else:
self.I0_texture = self.I0_texture_tagging_signed_XYZ_wMultiplicativeCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XYZ_wMultiplicativeCombination
else:
if ("-addComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_XYZ_wAdditiveCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XYZ_wAdditiveCombination
elif ("-diffComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_XYZ_wDifferentiableCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XYZ_wDifferentiableCombination
else:
self.I0_texture = self.I0_texture_tagging_XYZ_wMultiplicativeCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XYZ_wMultiplicativeCombination
else:
assert (0), "n_dim must be \"1\", \"2\" or \"3\". Aborting."
self.s = texture["s"]
elif (texture["type"].startswith("taggX")):
if ("-signed" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_X_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_X
else:
self.I0_texture = self.I0_texture_tagging_X_wGrad if (generate_image_gradient) else self.I0_texture_tagging_X
self.s = texture["s"]
elif (texture["type"].startswith("taggY")):
if ("-signed" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_Y_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_Y
else:
self.I0_texture = self.I0_texture_tagging_Y_wGrad if (generate_image_gradient) else self.I0_texture_tagging_Y
self.s = texture["s"]
elif (texture["type"].startswith("taggZ")):
if ("-signed" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_Z_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_Z
else:
self.I0_texture = self.I0_texture_tagging_Z_wGrad if (generate_image_gradient) else self.I0_texture_tagging_Z
self.s = texture["s"]
else:
assert (0), "texture type must be \"no\", \"tagging\", \"taggX\", \"taggY\" or \"taggZ\". Aborting."
# noise
if (noise["type"] == "no"):
self.I0_noise = self.I0_noise_no_wGrad if (generate_image_gradient) else self.I0_noise_no
elif (noise["type"] == "normal"):
self.I0_noise = self.I0_noise_normal_wGrad if (generate_image_gradient) else self.I0_noise_normal
self.avg = noise["avg"] if ("avg" in noise) else 0.
self.std = noise["stdev"]
else:
assert (0), "noise type must be \"no\" or \"normal\". Aborting."
def I0(self, X, I):
self.I0_structure(X, I)
self.I0_texture(X, I)
self.I0_noise(I)
def I0_wGrad(self, X, I, G):
self.I0_structure_wGrad(X, I, G)
self.I0_texture_wGrad(X, I, G)
self.I0_noise_wGrad(I, G)
def I0_structure_no(self, X, I):
I[0] = 1.
def I0_structure_no_wGrad(self, X, I, G):
self.I0_structure_no(X, I)
G[:] = 1. # MG 20180806: gradient is given by texture; here it is just indicator function
def I0_structure_box(self, X, I):
if all(numpy.greater_equal(X, self.Xmin)) and all(numpy.less_equal(X, self.Xmax)):
I[0] = 1.
else:
I[0] = 0.
def I0_structure_box_wGrad(self, X, I, G):
if all(numpy.greater_equal(X, self.Xmin)) and all(numpy.less_equal(X, self.Xmax)):
I[0] = 1.
G[:] = 1. # MG 20180806: gradient is given by texture; here it is just indicator function
else:
I[0] = 0.
G[:] = 0. # MG 20180806: gradient is given by texture; here it is just indicator function
def I0_structure_heart_2(self, X, I):
self.R = ((X[0]-self.L[0]/2)**2 + (X[1]-self.L[1]/2)**2)**(1./2)
if (self.R >= self.Ri) and (self.R <= self.Re):
I[0] = 1.
else:
I[0] = 0.
def I0_structure_heart_2_wGrad(self, X, I, G):
self.R = ((X[0]-self.L[0]/2)**2 + (X[1]-self.L[1]/2)**2)**(1./2)
if (self.R >= self.Ri) and (self.R <= self.Re):
I[0] = 1.
G[:] = 1. # MG 20180806: gradient is given by texture; here it is just indicator function
else:
I[0] = 0.
G[:] = 0. # MG 20180806: gradient is given by texture; here it is just indicator function
def I0_structure_heart_3(self, X, I):
self.R = ((X[0]-self.L[0]/2)**2 + (X[1]-self.L[1]/2)**2)**(1./2)
if (self.R >= self.Ri) and (self.R <= self.Re) and (X[2] >= self.Zmin) and (X[2] <= self.Zmax):
I[0] = 1.
else:
I[0] = 0.
def I0_structure_heart_3_wGrad(self, X, I, G):
self.R = ((X[0]-self.L[0]/2)**2 + (X[1]-self.L[1]/2)**2)**(1./2)
if (self.R >= self.Ri) and (self.R <= self.Re) and (X[2] >= self.Zmin) and (X[2] <= self.Zmax):
I[0] = 1.
G[:] = 1. # MG 20180806: gradient is given by texture; here it is just indicator function
else:
I[0] = 0.
G[:] = 0. # MG 20180806: gradient is given by texture; here it is just indicator function
def I0_texture_no(self, X, I):
I[0] *= 1.
def I0_texture_no_wGrad(self, X, I, G):
self.I0_texture_no(X, I)
G[:] *= 0.
def I0_texture_tagging_X(self, X, I):
I[0] *= abs(math.sin(math.pi*X[0]/self.s))
def I0_texture_tagging_X_wGrad(self, X, I, G):
self.I0_texture_tagging_X(X, I)
G[0] *= math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s)
G[1] *= 0.
G[2] *= 0.
def I0_texture_tagging_Y(self, X, I):
I[0] *= abs(math.sin(math.pi*X[1]/self.s))
def I0_texture_tagging_Y_wGrad(self, X, I, G):
self.I0_texture_tagging_Y(X, I)
G[0] *= 0.
G[1] *= math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s)
G[2] *= 0.
def I0_texture_tagging_Z(self, X, I):
I[0] *= abs(math.sin(math.pi*X[2]/self.s))
def I0_texture_tagging_Z_wGrad(self, X, I, G):
self.I0_texture_tagging_Z(X, I)
G[0] *= 0.
G[1] *= 0.
G[2] *= math.copysign(1, math.sin(math.pi*X[2]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[2]/self.s)
def I0_texture_tagging_XY_wDifferentiableCombination(self, X, I):
I[0] *= (1 + 3 * abs(math.sin(math.pi*X[0]/self.s))
* abs(math.sin(math.pi*X[1]/self.s)))**(1./2) - 1
def I0_texture_tagging_XY_wDifferentiableCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_XY_wDifferentiableCombination(X, I)
G[0] *= 3 * math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s) * abs(math.sin(math.pi*X[1]/self.s)) / 2 / (I[0] + 1)
G[1] *= 3 * math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) / 2 / (I[0] + 1)
G[2] *= 0.
def I0_texture_tagging_XY_wMultiplicativeCombination(self, X, I):
I[0] *= (abs(math.sin(math.pi*X[0]/self.s))
* abs(math.sin(math.pi*X[1]/self.s)))**(1./2)
def I0_texture_tagging_XY_wMultiplicativeCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_XY_wMultiplicativeCombination(X, I)
G[0] *= math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s) * abs(math.sin(math.pi*X[1]/self.s)) / 2 / I[0]
G[1] *= math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) / 2 / I[0]
G[2] *= 0.
def I0_texture_tagging_XYZ_wDifferentiableCombination(self, X, I):
I[0] *= (1 + 7 * abs(math.sin(math.pi*X[0]/self.s))
* abs(math.sin(math.pi*X[1]/self.s))
* abs(math.sin(math.pi*X[2]/self.s)))**(1./3) - 1
def I0_texture_tagging_XYZ_wDifferentiableCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_XYZ_wDifferentiableCombination(X, I)
G[0] *= 7 * math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s) * abs(math.sin(math.pi*X[1]/self.s)) * abs(math.sin(math.pi*X[2]/self.s)) / 3 / (I[0] + 1)
G[1] *= 7 * math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) * abs(math.sin(math.pi*X[2]/self.s)) / 3 / (I[0] + 1)
G[2] *= 7 * math.copysign(1, math.sin(math.pi*X[2]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[2]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) * abs(math.sin(math.pi*X[1]/self.s)) / 3 / (I[0] + 1)
def I0_texture_tagging_XYZ_wMultiplicativeCombination(self, X, I):
I[0] *= (abs(math.sin(math.pi*X[0]/self.s))
* abs(math.sin(math.pi*X[1]/self.s))
* abs(math.sin(math.pi*X[2]/self.s)))**(1./3)
def I0_texture_tagging_XYZ_wMultiplicativeCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_XYZ_wMultiplicativeCombination(X, I)
G[0] *= math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s) * abs(math.sin(math.pi*X[1]/self.s)) * abs(math.sin(math.pi*X[2]/self.s)) / 3 / I[0]**2
G[1] *= math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) * abs(math.sin(math.pi*X[2]/self.s)) / 3 / I[0]**2
G[2] *= math.copysign(1, math.sin(math.pi*X[2]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[2]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) * abs(math.sin(math.pi*X[1]/self.s)) / 3 / I[0]**2
def I0_texture_tagging_signed_X(self, X, I):
I[0] *= (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2
def I0_texture_tagging_signed_X_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_X(X, I)
G[0] *= (math.pi/self.s) * math.cos(math.pi*X[0]/self.s-math.pi/2) / 2
G[1] *= 0.
G[2] *= 0.
def I0_texture_tagging_signed_Y(self, X, I):
I[0] *= (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2
def I0_texture_tagging_signed_Y_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_Y(X, I)
G[0] *= 0.
G[1] *= (math.pi/self.s) * math.cos(math.pi*X[1]/self.s-math.pi/2) / 2
G[2] *= 0.
def I0_texture_tagging_signed_Z(self, X, I):
I[0] *= (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2
def I0_texture_tagging_signed_Z_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_Z(X, I)
G[0] *= 0.
G[1] *= 0.
G[2] *= (math.pi/self.s) * math.cos(math.pi*X[2]/self.s-math.pi/2) / 2
def I0_texture_tagging_signed_XY_wDifferentiableCombination(self, X, I):
I[0] *= (1 + 3 * (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2
* (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2)**(1./2) - 1
def I0_texture_tagging_signed_XY_wDifferentiableCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_XY_wDifferentiableCombination(X, I)
G[0] *= 3 * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s-math.pi/2)/2 * (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2 / 2 / (I[0] + 1)
G[1] *= 3 * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s-math.pi/2)/2 * (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2 / 2 / (I[0] + 1)
G[2] *= 0.
def I0_texture_tagging_signed_XY_wAdditiveCombination(self, X, I):
I[0] *= ((1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2
+ (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2) / 2
def I0_texture_tagging_signed_XY_wAdditiveCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_XY_wAdditiveCombination(X, I)
G[0] *= (math.pi/self.s) * math.cos(math.pi*X[0]/self.s-math.pi/2)/2 / 2
G[1] *= (math.pi/self.s) * math.cos(math.pi*X[1]/self.s-math.pi/2)/2 / 2
G[2] *= 0.
def I0_texture_tagging_signed_XYZ_wDifferentiableCombination(self, X, I):
I[0] *= (1 + 7 * (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2
* (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2
* (1+math.sin(math.pi*X[2]/self.s-math.pi/2))/2)**(1./3) - 1
def I0_texture_tagging_signed_XYZ_wDifferentiableCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_XYZ_wDifferentiableCombination(X, I)
G[0] *= 7 * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s-math.pi/2)/2 * (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2 * (1+math.sin(math.pi*X[2]/self.s-math.pi/2))/2 / 3 / (I[0] + 1)
G[1] *= 7 * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s-math.pi/2)/2 * (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2 * (1+math.sin(math.pi*X[2]/self.s-math.pi/2))/2 / 3 / (I[0] + 1)
G[2] *= 7 * (math.pi/self.s) * math.cos(math.pi*X[2]/self.s-math.pi/2)/2 * (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2 * (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2 / 3 / (I[0] + 1)
def I0_texture_tagging_signed_XYZ_wAdditiveCombination(self, X, I):
I[0] *= ((1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2
+ (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2
+ (1+math.sin(math.pi*X[2]/self.s-math.pi/2))/2) / 3
def I0_texture_tagging_signed_XYZ_wAdditiveCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_XYZ_wAdditiveCombination(X, I)
G[0] *= (math.pi/self.s) * math.cos(math.pi*X[0]/self.s-math.pi/2)/2 / 3
G[1] *= (math.pi/self.s) * math.cos(math.pi*X[1]/self.s-math.pi/2)/2 / 3
G[2] *= (math.pi/self.s) * math.cos(math.pi*X[2]/self.s-math.pi/2)/2 / 3
def I0_noise_no(self, I):
pass
def I0_noise_no_wGrad(self, I, G):
pass
def I0_noise_normal(self, I):
I[0] += random.normalvariate(self.avg, self.std)
def I0_noise_normal_wGrad(self, I, G):
self.I0_noise_normal(I)
G[:] += [2*random.normalvariate(self.avg, self.std) for k in xrange(len(G))]
################################################################################
class Mapping:
def __init__(self, images, structure, deformation, evolution, generate_image_gradient):
self.deformation = deformation
if (self.deformation["type"] == "no"):
self.init_t = self.init_t_no
self.X = self.X_no
self.x = self.x_no
elif (self.deformation["type"] == "translation"):
self.init_t = self.init_t_translation
self.X = self.X_translation
self.x = self.x_translation
self.D = numpy.empty(3)
elif (self.deformation["type"] == "rotation"):
self.init_t = self.init_t_rotation
self.X = self.X_rotation
self.x = self.x_rotation
self.C = numpy.empty(3)
self.R = numpy.empty((3,3))
self.Rinv = numpy.empty((3,3))
elif (self.deformation["type"] == "homogeneous"):
self.init_t = self.init_t_homogeneous
self.X = self.X_homogeneous
self.x = self.x_homogeneous
elif (self.deformation["type"] == "heart"):
assert (structure["type"] == "heart"), "structure type must be \"heart\" for \"heart\" type deformation. Aborting."
self.init_t = self.init_t_heart
self.X = self.X_heart
self.x = self.x_heart
self.x_inplane = numpy.empty(2)
self.X_inplane = numpy.empty(2)
self.rt = numpy.empty(2)
self.RT = numpy.empty(2)
self.L = images["L"]
self.Ri = structure["Ri"]
self.Re = structure["Re"]
self.R = numpy.empty((3,3))
else:
assert (0), "deformation type must be \"no\", \"translation\", \"rotation\", \"homogeneous\" or \"heart\". Aborting."
if (evolution["type"] == "linear"):
self.phi = self.phi_linear
elif (evolution["type"] == "sine"):
self.phi = self.phi_sine
self.T = evolution["T"]
else:
assert (0), "evolution ("+evolution["type"]+") type must be \"linear\" or \"sine\". Aborting."
def phi_linear(self, t):
return t
def phi_sine(self, t):
return math.sin(math.pi*t/self.T)**2
def init_t_no(self, t):
pass
def init_t_translation(self, t):
self.D[0] = self.deformation["Dx"] if ("Dx" in self.deformation) else 0.
self.D[1] = self.deformation["Dy"] if ("Dy" in self.deformation) else 0.
self.D[2] = self.deformation["Dz"] if ("Dz" in self.deformation) else 0.
self.D *= self.phi(t)
def init_t_rotation(self, t):
self.C[0] = self.deformation["Cx"] if ("Cx" in self.deformation) else 0.
self.C[1] = self.deformation["Cy"] if ("Cy" in self.deformation) else 0.
self.C[2] = self.deformation["Cz"] if ("Cz" in self.deformation) else 0.
Rx = self.deformation["Rx"]*math.pi/180*self.phi(t) if ("Rx" in self.deformation) else 0.
Ry = self.deformation["Ry"]*math.pi/180*self.phi(t) if ("Ry" in self.deformation) else 0.
Rz = self.deformation["Rz"]*math.pi/180*self.phi(t) if ("Rz" in self.deformation) else 0.
RRx = numpy.array([[ 1. , 0. , 0. ],
[ 0. , +math.cos(Rx), -math.sin(Rx)],
[ 0. , +math.sin(Rx), +math.cos(Rx)]])
RRy = numpy.array([[+math.cos(Ry), 0. , +math.sin(Ry)],
[ 0. , 1. , 0. ],
[-math.sin(Ry), 0. , +math.cos(Ry)]])
RRz = numpy.array([[+math.cos(Rz), -math.sin(Rz), 0. ],
[+math.sin(Rz), +math.cos(Rz), 0. ],
[ 0. , 0. , 1. ]])
self.R[:,:] = numpy.dot(numpy.dot(RRx, RRy), RRz)
self.Rinv[:,:] = numpy.linalg.inv(self.R)
def init_t_homogeneous(self, t):
if (any(E in self.deformation for E in ("Exx", "Eyy", "Ezz"))): # build F from E
Exx = self.deformation["Exx"] if ("Exx" in self.deformation) else 0.
Eyy = self.deformation["Eyy"] if ("Eyy" in self.deformation) else 0.
Ezz = self.deformation["Ezz"] if ("Ezz" in self.deformation) else 0.
self.F = numpy.array([[Exx, 0., 0.],
[ 0., Eyy, 0.],
[ 0., 0., Ezz]])*self.phi(t)
self.F *= 2
self.F += numpy.eye(3)
w, v = numpy.linalg.eig(self.F)
# assert (numpy.diag(numpy.dot(numpy.dot(numpy.transpose(v), self.F), v)) == w).all(), str(numpy.dot(numpy.dot(numpy.transpose(v), self.F), v))+" ≠ "+str(numpy.diag(w))+". Aborting."
self.F = numpy.dot(numpy.dot(v, numpy.diag(numpy.sqrt(w))), numpy.transpose(v))
else:
Fxx = self.deformation["Fxx"] if ("Fxx" in self.deformation) else 0.
Fyy = self.deformation["Fyy"] if ("Fyy" in self.deformation) else 0.
Fzz = self.deformation["Fzz"] if ("Fzz" in self.deformation) else 0.
Fxy = self.deformation["Fxy"] if ("Fxy" in self.deformation) else 0.
Fyx = self.deformation["Fyx"] if ("Fyx" in self.deformation) else 0.
Fyz = self.deformation["Fyz"] if ("Fyz" in self.deformation) else 0.
Fzy = self.deformation["Fzy"] if ("Fzy" in self.deformation) else 0.
Fzx = self.deformation["Fzx"] if ("Fzx" in self.deformation) else 0.
Fxz = self.deformation["Fxz"] if ("Fxz" in self.deformation) else 0.
self.F = numpy.eye(3) + (numpy.array([[Fxx, Fxy, Fxz],
[Fyx, Fyy, Fyz],
[Fzx, Fzy, Fzz]])-numpy.eye(3))*self.phi(t)
self.Finv = numpy.linalg.inv(self.F)
def init_t_heart(self, t):
self.dRi = self.deformation["dRi"]*self.phi(t) if ("dRi" in self.deformation) else 0.
self.dRe = self.deformation["dRi"]*self.phi(t) if ("dRi" in self.deformation) else 0.
self.dTi = self.deformation["dTi"]*self.phi(t) if ("dTi" in self.deformation) else 0.
self.dTe = self.deformation["dTe"]*self.phi(t) if ("dTe" in self.deformation) else 0.
self.A = numpy.array([[1.-(self.dRi-self.dRe)/(self.Re-self.Ri), 0.],
[ -(self.dTi-self.dTe)/(self.Re-self.Ri), 1.]])
self.Ainv = numpy.linalg.inv(self.A)
self.B = numpy.array([(1.+self.Ri/(self.Re-self.Ri))*self.dRi-self.Ri/(self.Re-self.Ri)*self.dRe,
(1.+self.Ri/(self.Re-self.Ri))*self.dTi-self.Ri/(self.Re-self.Ri)*self.dTe])
def X_no(self, x, X, Finv=None):
X[:] = x
if (Finv is not None): Finv[:,:] = numpy.identity(numpy.sqrt(numpy.size(Finv)))
def X_translation(self, x, X, Finv=None):
X[:] = x - self.D
if (Finv is not None): Finv[:,:] = numpy.identity(numpy.sqrt(numpy.size(Finv)))
def X_rotation(self, x, X, Finv=None):
X[:] = numpy.dot(self.Rinv, x - self.C) + self.C
if (Finv is not None): Finv[:,:] = self.Rinv
def X_homogeneous(self, x, X, Finv=None):
X[:] = numpy.dot(self.Finv, x)
if (Finv is not None): Finv[:,:] = self.Finv
def X_heart(self, x, X, Finv=None):
#print "x = "+str(x)
self.x_inplane[0] = x[0] - self.L[0]/2
self.x_inplane[1] = x[1] - self.L[1]/2
#print "x_inplane = "+str(self.x_inplane)
self.rt[0] = numpy.linalg.norm(self.x_inplane)
self.rt[1] = math.atan2(self.x_inplane[1], self.x_inplane[0])
#print "rt = "+str(self.rt)
self.RT[:] = numpy.dot(self.Ainv, self.rt-self.B)
#print "RT = "+str(self.RT)
X[0] = self.RT[0] * math.cos(self.RT[1]) + self.L[0]/2
X[1] = self.RT[0] * math.sin(self.RT[1]) + self.L[1]/2
X[2] = x[2]
#print "X = "+str(X)
if (Finv is not None):
Finv[0,0] = 1.+(self.dRe-self.dRi)/(self.Re-self.Ri)
Finv[0,1] = 0.
Finv[0,2] = 0.
Finv[1,0] = (self.dTe-self.dTi)/(self.Re-self.Ri)*self.rt[0]
Finv[1,1] = self.rt[0]/self.RT[0]
Finv[1,2] = 0.
Finv[2,0] = 0.
Finv[2,1] = 0.
Finv[2,2] = 1.
#print "F = "+str(Finv)
Finv[:,:] = numpy.linalg.inv(Finv)
#print "Finv = "+str(Finv)
self.R[0,0] = +math.cos(self.RT[1])
self.R[0,1] = +math.sin(self.RT[1])
self.R[0,2] = 0.
self.R[1,0] = -math.sin(self.RT[1])
self.R[1,1] = +math.cos(self.RT[1])
self.R[1,2] = 0.
self.R[2,0] = 0.
self.R[2,1] = 0.
self.R[2,2] = 1.
#print "R = "+str(self.R)
Finv[:] = numpy.dot(numpy.transpose(self.R), numpy.dot(Finv, self.R))
#print "Finv = "+str(Finv)
def x_no(self, X, x, F=None):
x[:] = X
if (F is not None): F[:,:] = numpy.identity(numpy.sqrt(numpy.size(F)))
def x_translation(self, X, x, F=None):
x[:] = X + self.D
if (F is not None): F[:,:] = numpy.identity(numpy.sqrt(numpy.size(F)))
def x_rotation(self, X, x, F=None):
x[:] = numpy.dot(self.R, X - self.C) + self.C
if (F is not None): F[:,:] = self.R
def x_homogeneous(self, X, x, F=None):
x[:] = numpy.dot(self.F, X)
if (F is not None): F[:,:] = self.F
def x_heart(self, X, x, F=None):
#print "X = "+str(X)
self.X_inplane[0] = X[0] - self.L[0]/2
self.X_inplane[1] = X[1] - self.L[1]/2
#print "X_inplane = "+str(self.X_inplane)
self.RT[0] = numpy.linalg.norm(self.X_inplane)
self.RT[1] = math.atan2(self.X_inplane[1], self.X_inplane[0])
#print "RT = "+str(self.RT)
self.rt[:] = numpy.dot(self.A, self.RT) + self.B
#print "rt = "+str(self.rt)
x[0] = self.rt[0] * math.cos(self.rt[1]) + self.L[0]/2
x[1] = self.rt[0] * math.sin(self.rt[1]) + self.L[1]/2
x[2] = X[2]
#print "x = "+str(x)
if (F is not None):
F[0,0] = 1.+(self.dRe-self.dRi)/(self.Re-self.Ri)
F[0,1] = 0.
F[0,2] = 0.
F[1,0] = (self.dTe-self.dTi)/(self.Re-self.Ri)*self.rt[0]
F[1,1] = self.rt[0]/self.RT[0]
F[1,2] = 0.
F[2,0] = 0.
F[2,1] = 0.
F[2,2] = 1.
#print "F = "+str(F)
self.R[0,0] = +math.cos(self.RT[1])
self.R[0,1] = +math.sin(self.RT[1])
self.R[0,2] = 0.
self.R[1,0] = -math.sin(self.RT[1])
self.R[1,1] = +math.cos(self.RT[1])
self.R[1,2] = 0.
self.R[2,0] = 0.
self.R[2,1] = 0.
self.R[2,2] = 1.
F[:] = numpy.dot(numpy.transpose(self.R), numpy.dot(F, self.R))
#print "F = "+str(F)
################################################################################ ################################################################################
...@@ -699,8 +67,8 @@ def generateImages( ...@@ -699,8 +67,8 @@ def generateImages(
assert ("n_integration" not in images),\ assert ("n_integration" not in images),\
"\"n_integration\" has been deprecated. Use \"resampling\" instead. Aborting." "\"n_integration\" has been deprecated. Use \"resampling\" instead. Aborting."
if ("resampling" not in images): if ("resampling_factors" not in images):
images["resampling"] = [1]*images["n_dim"] images["resampling_factors"] = [1]*images["n_dim"]
if ("zfill" not in images): if ("zfill" not in images):
images["zfill"] = len(str(images["n_frames"])) images["zfill"] = len(str(images["n_frames"]))
if ("ext" not in images): if ("ext" not in images):
...@@ -725,20 +93,20 @@ def generateImages( ...@@ -725,20 +93,20 @@ def generateImages(
vtk_image = vtk.vtkImageData() vtk_image = vtk.vtkImageData()
if (images["n_dim"] == 1): if (images["n_dim"] == 1):
vtk_image.SetExtent([0, images["n_voxels"][0]*images["resampling"][0]-1, 0, 0, 0, 0]) vtk_image.SetExtent([0, images["n_voxels"][0]*images["resampling_factors"][0]-1, 0, 0, 0, 0])
elif (images["n_dim"] == 2): elif (images["n_dim"] == 2):
vtk_image.SetExtent([0, images["n_voxels"][0]*images["resampling"][0]-1, 0, images["n_voxels"][1]*images["resampling"][1]-1, 0, 0]) vtk_image.SetExtent([0, images["n_voxels"][0]*images["resampling_factors"][0]-1, 0, images["n_voxels"][1]*images["resampling_factors"][1]-1, 0, 0])
elif (images["n_dim"] == 3): elif (images["n_dim"] == 3):
vtk_image.SetExtent([0, images["n_voxels"][0]*images["resampling"][0]-1, 0, images["n_voxels"][1]*images["resampling"][1]-1, 0, images["n_voxels"][2]*images["resampling"][2]-1]) vtk_image.SetExtent([0, images["n_voxels"][0]*images["resampling_factors"][0]-1, 0, images["n_voxels"][1]*images["resampling_factors"][1]-1, 0, images["n_voxels"][2]*images["resampling_factors"][2]-1])
else: else:
assert (0), "n_dim must be \"1\", \"2\" or \"3\". Aborting." assert (0), "n_dim must be \"1\", \"2\" or \"3\". Aborting."
if (images["n_dim"] == 1): if (images["n_dim"] == 1):
spacing = numpy.array([images["L"][0]/images["n_voxels"][0]/images["resampling"][0], 1., 1.]) spacing = numpy.array([images["L"][0]/images["n_voxels"][0]/images["resampling_factors"][0], 1., 1.])
elif (images["n_dim"] == 2): elif (images["n_dim"] == 2):
spacing = numpy.array([images["L"][0]/images["n_voxels"][0]/images["resampling"][0], images["L"][1]/images["n_voxels"][1]/images["resampling"][1], 1.]) spacing = numpy.array([images["L"][0]/images["n_voxels"][0]/images["resampling_factors"][0], images["L"][1]/images["n_voxels"][1]/images["resampling_factors"][1], 1.])
elif (images["n_dim"] == 3): elif (images["n_dim"] == 3):
spacing = numpy.array([images["L"][0]/images["n_voxels"][0]/images["resampling"][0], images["L"][1]/images["n_voxels"][1]/images["resampling"][1], images["L"][2]/images["n_voxels"][2]/images["resampling"][2]]) spacing = numpy.array([images["L"][0]/images["n_voxels"][0]/images["resampling_factors"][0], images["L"][1]/images["n_voxels"][1]/images["resampling_factors"][1], images["L"][2]/images["n_voxels"][2]/images["resampling_factors"][2]])
vtk_image.SetSpacing(spacing) vtk_image.SetSpacing(spacing)
if (images["n_dim"] == 1): if (images["n_dim"] == 1):
...@@ -808,42 +176,23 @@ def generateImages( ...@@ -808,42 +176,23 @@ def generateImages(
image=vtk_gradient, image=vtk_gradient,
filename=images["folder"]+"/"+images["basename"]+"-grad"+"_"+str(k_frame).zfill(images["zfill"])+"."+images["ext"], filename=images["folder"]+"/"+images["basename"]+"-grad"+"_"+str(k_frame).zfill(images["zfill"])+"."+images["ext"],
verbose=verbose-1) verbose=verbose-1)
print "global_min = "+str(global_min)
print "global_max = "+str(global_max)
if (images["resampling_factors"] == [1]*images["n_dim"]):
resampling = False
else:
resampling = True
ddic.resample_images(
images_folder=images["folder"],
images_basename=images["basename"],
resampling_factors=images["resampling_factors"],
write_temp_images=1)
if (images["data_type"] in ("float")): if (images["data_type"] in ("float")):
pass pass
elif (images["data_type"] in ("unsigned char", "unsigned short", "unsigned int", "unsigned long", "unsigned float", "uint8", "uint16", "uint32", "uint64", "ufloat")): elif (images["data_type"] in ("unsigned char", "unsigned short", "unsigned int", "unsigned long", "unsigned float", "uint8", "uint16", "uint32", "uint64", "ufloat")):
#print "global_min = "+str(global_min) ddic.normalize_images(
#print "global_max = "+str(global_max) images_folder=images["folder"],
shifter = vtk.vtkImageShiftScale() images_basename=images["basename"]+("_resampled"*(resampling)),
shifter.SetShift(-global_min) images_datatype=images["data_type"])
if (images["data_type"] in ("unsigned char", "uint8")):
shifter.SetScale(float(2**8-1)/(global_max-global_min))
shifter.SetOutputScalarTypeToUnsignedChar()
elif (images["data_type"] in ("unsigned short", "uint16")):
shifter.SetScale(float(2**16-1)/(global_max-global_min))
shifter.SetOutputScalarTypeToUnsignedShort()
elif (images["data_type"] in ("unsigned int", "uint32")):
shifter.SetScale(float(2**32-1)/(global_max-global_min))
shifter.SetOutputScalarTypeToUnsignedInt()
elif (images["data_type"] in ("unsigned long", "uint64")):
shifter.SetScale(float(2**64-1)/(global_max-global_min))
shifter.SetOutputScalarTypeToUnsignedLong()
elif (images["data_type"] in ("unsigned float", "ufloat")):
shifter.SetScale(1./(global_max-global_min))
shifter.SetOutputScalarTypeToFloat()
for k_frame in xrange(images["n_frames"]):
vtk_image = myvtk.readImage(
filename=images["folder"]+"/"+images["basename"]+"_"+str(k_frame).zfill(images["zfill"])+"."+images["ext"],
verbose=verbose-1)
if (vtk.vtkVersion.GetVTKMajorVersion() >= 6):
shifter.SetInputData(vtk_image)
else:
shifter.SetInput(vtk_image)
shifter.Update()
vtk_image = shifter.GetOutput()
myvtk.writeImage(
image=vtk_image,
filename=images["folder"]+"/"+images["basename"]+"_"+str(k_frame).zfill(images["zfill"])+"."+images["ext"],
verbose=verbose-1)
else:
assert (0), "Wrong data type. Aborting."
generate_images_Image.py 0 → 100644
+ 358
− 0
View file @ c2d3607a
#coding=utf8
################################################################################
### ###
### Created by Martin Genet, 2016-2019 ###
### ###
### École Polytechnique, Palaiseau, France ###
### ###
################################################################################
import glob
import math
import numpy
import os
import random
import vtk
import myPythonLibrary as mypy
import myVTKPythonLibrary as myvtk
import dolfin_dic as ddic
################################################################################
class Image():
def __init__(self, images, structure, texture, noise, generate_image_gradient=False):
self.L = images["L"]
# structure
if (structure["type"] == "no"):
self.I0_structure = self.I0_structure_no_wGrad if (generate_image_gradient) else self.I0_structure_no
elif (structure["type"] == "box"):
self.I0_structure = self.I0_structure_box_wGrad if (generate_image_gradient) else self.I0_structure_box
self.Xmin = structure["Xmin"]
self.Xmax = structure["Xmax"]
elif (structure["type"] == "heart"):
if (images["n_dim"] == 2):
self.I0_structure = self.I0_structure_heart_2_wGrad if (generate_image_gradient) else self.I0_structure_heart_2
self.R = float()
self.Ri = structure["Ri"]
self.Re = structure["Re"]
elif (images["n_dim"] == 3):
self.I0_structure = self.I0_structure_heart_3_wGrad if (generate_image_gradient) else self.I0_structure_heart_3
self.R = float()
self.Ri = structure["Ri"]
self.Re = structure["Re"]
self.Zmin = structure.Zmin if ("Zmin" in structure) else 0.
self.Zmax = structure.Zmax if ("Zmax" in structure) else images["L"][2]
else:
assert (0), "n_dim must be \"2\" or \"3 for \"heart\" type structure. Aborting."
else:
assert (0), "structure type must be \"no\", \"box\" or \"heart\". Aborting."
# texture
if (texture["type"] == "no"):
self.I0_texture = self.I0_texture_no_wGrad if (generate_image_gradient) else self.I0_texture_no
elif (texture["type"].startswith("tagging")):
if (images["n_dim"] == 1):
if ("-signed" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_X_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_X
else:
self.I0_texture = self.I0_texture_tagging_X_wGrad if (generate_image_gradient) else self.I0_texture_tagging_X
elif (images["n_dim"] == 2):
if ("-signed" in texture["type"]):
if ("-addComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_XY_wAdditiveCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XY_wAdditiveCombination
elif ("-diffComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_XY_wDifferentiableCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XY_wDifferentiableCombination
else:
self.I0_texture = self.I0_texture_tagging_signed_XY_wMultiplicativeCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XY_wMultiplicativeCombination
else:
if ("-addComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_XY_wAdditiveCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XY_wAdditiveCombination
elif ("-diffComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_XY_wDifferentiableCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XY_wDifferentiableCombination
else:
self.I0_texture = self.I0_texture_tagging_XY_wMultiplicativeCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XY_wMultiplicativeCombination
elif (images["n_dim"] == 3):
if ("-signed" in texture["type"]):
if ("-addComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_XYZ_wAdditiveCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XYZ_wAdditiveCombination
elif ("-diffComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_XYZ_wDifferentiableCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XYZ_wDifferentiableCombination
else:
self.I0_texture = self.I0_texture_tagging_signed_XYZ_wMultiplicativeCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_XYZ_wMultiplicativeCombination
else:
if ("-addComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_XYZ_wAdditiveCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XYZ_wAdditiveCombination
elif ("-diffComb" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_XYZ_wDifferentiableCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XYZ_wDifferentiableCombination
else:
self.I0_texture = self.I0_texture_tagging_XYZ_wMultiplicativeCombination_wGrad if (generate_image_gradient) else self.I0_texture_tagging_XYZ_wMultiplicativeCombination
else:
assert (0), "n_dim must be \"1\", \"2\" or \"3\". Aborting."
self.s = texture["s"]
elif (texture["type"].startswith("taggX")):
if ("-signed" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_X_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_X
else:
self.I0_texture = self.I0_texture_tagging_X_wGrad if (generate_image_gradient) else self.I0_texture_tagging_X
self.s = texture["s"]
elif (texture["type"].startswith("taggY")):
if ("-signed" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_Y_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_Y
else:
self.I0_texture = self.I0_texture_tagging_Y_wGrad if (generate_image_gradient) else self.I0_texture_tagging_Y
self.s = texture["s"]
elif (texture["type"].startswith("taggZ")):
if ("-signed" in texture["type"]):
self.I0_texture = self.I0_texture_tagging_signed_Z_wGrad if (generate_image_gradient) else self.I0_texture_tagging_signed_Z
else:
self.I0_texture = self.I0_texture_tagging_Z_wGrad if (generate_image_gradient) else self.I0_texture_tagging_Z
self.s = texture["s"]
else:
assert (0), "texture type must be \"no\", \"tagging\", \"taggX\", \"taggY\" or \"taggZ\". Aborting."
# noise
if (noise["type"] == "no"):
self.I0_noise = self.I0_noise_no_wGrad if (generate_image_gradient) else self.I0_noise_no
elif (noise["type"] == "normal"):
self.I0_noise = self.I0_noise_normal_wGrad if (generate_image_gradient) else self.I0_noise_normal
self.avg = noise["avg"] if ("avg" in noise) else 0.
self.std = noise["stdev"]
else:
assert (0), "noise type must be \"no\" or \"normal\". Aborting."
def I0(self, X, I):
self.I0_structure(X, I)
self.I0_texture(X, I)
self.I0_noise(I)
def I0_wGrad(self, X, I, G):
self.I0_structure_wGrad(X, I, G)
self.I0_texture_wGrad(X, I, G)
self.I0_noise_wGrad(I, G)
def I0_structure_no(self, X, I):
I[0] = 1.
def I0_structure_no_wGrad(self, X, I, G):
self.I0_structure_no(X, I)
G[:] = 1. # MG 20180806: gradient is given by texture; here it is just indicator function
def I0_structure_box(self, X, I):
if all(numpy.greater_equal(X, self.Xmin)) and all(numpy.less_equal(X, self.Xmax)):
I[0] = 1.
else:
I[0] = 0.
def I0_structure_box_wGrad(self, X, I, G):
if all(numpy.greater_equal(X, self.Xmin)) and all(numpy.less_equal(X, self.Xmax)):
I[0] = 1.
G[:] = 1. # MG 20180806: gradient is given by texture; here it is just indicator function
else:
I[0] = 0.
G[:] = 0. # MG 20180806: gradient is given by texture; here it is just indicator function
def I0_structure_heart_2(self, X, I):
self.R = ((X[0]-self.L[0]/2)**2 + (X[1]-self.L[1]/2)**2)**(1./2)
if (self.R >= self.Ri) and (self.R <= self.Re):
I[0] = 1.
else:
I[0] = 0.
def I0_structure_heart_2_wGrad(self, X, I, G):
self.R = ((X[0]-self.L[0]/2)**2 + (X[1]-self.L[1]/2)**2)**(1./2)
if (self.R >= self.Ri) and (self.R <= self.Re):
I[0] = 1.
G[:] = 1. # MG 20180806: gradient is given by texture; here it is just indicator function
else:
I[0] = 0.
G[:] = 0. # MG 20180806: gradient is given by texture; here it is just indicator function
def I0_structure_heart_3(self, X, I):
self.R = ((X[0]-self.L[0]/2)**2 + (X[1]-self.L[1]/2)**2)**(1./2)
if (self.R >= self.Ri) and (self.R <= self.Re) and (X[2] >= self.Zmin) and (X[2] <= self.Zmax):
I[0] = 1.
else:
I[0] = 0.
def I0_structure_heart_3_wGrad(self, X, I, G):
self.R = ((X[0]-self.L[0]/2)**2 + (X[1]-self.L[1]/2)**2)**(1./2)
if (self.R >= self.Ri) and (self.R <= self.Re) and (X[2] >= self.Zmin) and (X[2] <= self.Zmax):
I[0] = 1.
G[:] = 1. # MG 20180806: gradient is given by texture; here it is just indicator function
else:
I[0] = 0.
G[:] = 0. # MG 20180806: gradient is given by texture; here it is just indicator function
def I0_texture_no(self, X, I):
I[0] *= 1.
def I0_texture_no_wGrad(self, X, I, G):
self.I0_texture_no(X, I)
G[:] *= 0.
def I0_texture_tagging_X(self, X, I):
I[0] *= abs(math.sin(math.pi*X[0]/self.s))
def I0_texture_tagging_X_wGrad(self, X, I, G):
self.I0_texture_tagging_X(X, I)
G[0] *= math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s)
G[1] *= 0.
G[2] *= 0.
def I0_texture_tagging_Y(self, X, I):
I[0] *= abs(math.sin(math.pi*X[1]/self.s))
def I0_texture_tagging_Y_wGrad(self, X, I, G):
self.I0_texture_tagging_Y(X, I)
G[0] *= 0.
G[1] *= math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s)
G[2] *= 0.
def I0_texture_tagging_Z(self, X, I):
I[0] *= abs(math.sin(math.pi*X[2]/self.s))
def I0_texture_tagging_Z_wGrad(self, X, I, G):
self.I0_texture_tagging_Z(X, I)
G[0] *= 0.
G[1] *= 0.
G[2] *= math.copysign(1, math.sin(math.pi*X[2]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[2]/self.s)
def I0_texture_tagging_XY_wDifferentiableCombination(self, X, I):
I[0] *= (1 + 3 * abs(math.sin(math.pi*X[0]/self.s))
* abs(math.sin(math.pi*X[1]/self.s)))**(1./2) - 1
def I0_texture_tagging_XY_wDifferentiableCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_XY_wDifferentiableCombination(X, I)
G[0] *= 3 * math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s) * abs(math.sin(math.pi*X[1]/self.s)) / 2 / (I[0] + 1)
G[1] *= 3 * math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) / 2 / (I[0] + 1)
G[2] *= 0.
def I0_texture_tagging_XY_wAdditiveCombination(self, X, I):
I[0] *= (abs(math.sin(math.pi*X[0]/self.s))
+ abs(math.sin(math.pi*X[1]/self.s)))/2
def I0_texture_tagging_XY_wAdditiveCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_XY_wAdditiveCombination(X, I)
G[0] *= math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s) / 2
G[1] *= math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s) / 2
G[2] *= 0.
def I0_texture_tagging_XY_wMultiplicativeCombination(self, X, I):
I[0] *= (abs(math.sin(math.pi*X[0]/self.s))
* abs(math.sin(math.pi*X[1]/self.s)))**(1./2)
def I0_texture_tagging_XY_wMultiplicativeCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_XY_wMultiplicativeCombination(X, I)
G[0] *= math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s) * abs(math.sin(math.pi*X[1]/self.s)) / 2 / I[0]
G[1] *= math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) / 2 / I[0]
G[2] *= 0.
def I0_texture_tagging_XYZ_wDifferentiableCombination(self, X, I):
I[0] *= (1 + 7 * abs(math.sin(math.pi*X[0]/self.s))
* abs(math.sin(math.pi*X[1]/self.s))
* abs(math.sin(math.pi*X[2]/self.s)))**(1./3) - 1
def I0_texture_tagging_XYZ_wDifferentiableCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_XYZ_wDifferentiableCombination(X, I)
G[0] *= 7 * math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s) * abs(math.sin(math.pi*X[1]/self.s)) * abs(math.sin(math.pi*X[2]/self.s)) / 3 / (I[0] + 1)
G[1] *= 7 * math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) * abs(math.sin(math.pi*X[2]/self.s)) / 3 / (I[0] + 1)
G[2] *= 7 * math.copysign(1, math.sin(math.pi*X[2]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[2]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) * abs(math.sin(math.pi*X[1]/self.s)) / 3 / (I[0] + 1)
def I0_texture_tagging_XYZ_wMultiplicativeCombination(self, X, I):
I[0] *= (abs(math.sin(math.pi*X[0]/self.s))
* abs(math.sin(math.pi*X[1]/self.s))
* abs(math.sin(math.pi*X[2]/self.s)))**(1./3)
def I0_texture_tagging_XYZ_wMultiplicativeCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_XYZ_wMultiplicativeCombination(X, I)
G[0] *= math.copysign(1, math.sin(math.pi*X[0]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s) * abs(math.sin(math.pi*X[1]/self.s)) * abs(math.sin(math.pi*X[2]/self.s)) / 3 / I[0]**2
G[1] *= math.copysign(1, math.sin(math.pi*X[1]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) * abs(math.sin(math.pi*X[2]/self.s)) / 3 / I[0]**2
G[2] *= math.copysign(1, math.sin(math.pi*X[2]/self.s)) * (math.pi/self.s) * math.cos(math.pi*X[2]/self.s) * abs(math.sin(math.pi*X[0]/self.s)) * abs(math.sin(math.pi*X[1]/self.s)) / 3 / I[0]**2
def I0_texture_tagging_signed_X(self, X, I):
I[0] *= (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2
def I0_texture_tagging_signed_X_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_X(X, I)
G[0] *= (math.pi/self.s) * math.cos(math.pi*X[0]/self.s-math.pi/2) / 2
G[1] *= 0.
G[2] *= 0.
def I0_texture_tagging_signed_Y(self, X, I):
I[0] *= (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2
def I0_texture_tagging_signed_Y_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_Y(X, I)
G[0] *= 0.
G[1] *= (math.pi/self.s) * math.cos(math.pi*X[1]/self.s-math.pi/2) / 2
G[2] *= 0.
def I0_texture_tagging_signed_Z(self, X, I):
I[0] *= (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2
def I0_texture_tagging_signed_Z_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_Z(X, I)
G[0] *= 0.
G[1] *= 0.
G[2] *= (math.pi/self.s) * math.cos(math.pi*X[2]/self.s-math.pi/2) / 2
def I0_texture_tagging_signed_XY_wDifferentiableCombination(self, X, I):
I[0] *= (1 + 3 * (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2
* (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2)**(1./2) - 1
def I0_texture_tagging_signed_XY_wDifferentiableCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_XY_wDifferentiableCombination(X, I)
G[0] *= 3 * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s-math.pi/2)/2 * (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2 / 2 / (I[0] + 1)
G[1] *= 3 * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s-math.pi/2)/2 * (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2 / 2 / (I[0] + 1)
G[2] *= 0.
def I0_texture_tagging_signed_XY_wAdditiveCombination(self, X, I):
I[0] *= ((1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2
+ (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2) / 2
def I0_texture_tagging_signed_XY_wAdditiveCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_XY_wAdditiveCombination(X, I)
G[0] *= (math.pi/self.s) * math.cos(math.pi*X[0]/self.s-math.pi/2)/2 / 2
G[1] *= (math.pi/self.s) * math.cos(math.pi*X[1]/self.s-math.pi/2)/2 / 2
G[2] *= 0.
def I0_texture_tagging_signed_XYZ_wDifferentiableCombination(self, X, I):
I[0] *= (1 + 7 * (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2
* (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2
* (1+math.sin(math.pi*X[2]/self.s-math.pi/2))/2)**(1./3) - 1
def I0_texture_tagging_signed_XYZ_wDifferentiableCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_XYZ_wDifferentiableCombination(X, I)
G[0] *= 7 * (math.pi/self.s) * math.cos(math.pi*X[0]/self.s-math.pi/2)/2 * (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2 * (1+math.sin(math.pi*X[2]/self.s-math.pi/2))/2 / 3 / (I[0] + 1)
G[1] *= 7 * (math.pi/self.s) * math.cos(math.pi*X[1]/self.s-math.pi/2)/2 * (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2 * (1+math.sin(math.pi*X[2]/self.s-math.pi/2))/2 / 3 / (I[0] + 1)
G[2] *= 7 * (math.pi/self.s) * math.cos(math.pi*X[2]/self.s-math.pi/2)/2 * (1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2 * (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2 / 3 / (I[0] + 1)
def I0_texture_tagging_signed_XYZ_wAdditiveCombination(self, X, I):
I[0] *= ((1+math.sin(math.pi*X[0]/self.s-math.pi/2))/2
+ (1+math.sin(math.pi*X[1]/self.s-math.pi/2))/2
+ (1+math.sin(math.pi*X[2]/self.s-math.pi/2))/2) / 3
def I0_texture_tagging_signed_XYZ_wAdditiveCombination_wGrad(self, X, I, G):
self.I0_texture_tagging_signed_XYZ_wAdditiveCombination(X, I)
G[0] *= (math.pi/self.s) * math.cos(math.pi*X[0]/self.s-math.pi/2)/2 / 3
G[1] *= (math.pi/self.s) * math.cos(math.pi*X[1]/self.s-math.pi/2)/2 / 3
G[2] *= (math.pi/self.s) * math.cos(math.pi*X[2]/self.s-math.pi/2)/2 / 3
def I0_noise_no(self, I):
pass
def I0_noise_no_wGrad(self, I, G):
pass
def I0_noise_normal(self, I):
I[0] += random.normalvariate(self.avg, self.std)
def I0_noise_normal_wGrad(self, I, G):
self.I0_noise_normal(I)
G[:] += [2*random.normalvariate(self.avg, self.std) for k in xrange(len(G))]
generate_images_Mapping.py 0 → 100644
+ 254
− 0
View file @ c2d3607a
#coding=utf8
################################################################################
### ###
### Created by Martin Genet, 2016-2019 ###
### ###
### École Polytechnique, Palaiseau, France ###
### ###
################################################################################
import glob
import math
import numpy
import os
import random
import vtk
import myPythonLibrary as mypy
import myVTKPythonLibrary as myvtk
import dolfin_dic as ddic
################################################################################
class Mapping:
def __init__(self, images, structure, deformation, evolution, generate_image_gradient):
self.deformation = deformation
if (self.deformation["type"] == "no"):
self.init_t = self.init_t_no
self.X = self.X_no
self.x = self.x_no
elif (self.deformation["type"] == "translation"):
self.init_t = self.init_t_translation
self.X = self.X_translation
self.x = self.x_translation
self.D = numpy.empty(3)
elif (self.deformation["type"] == "rotation"):
self.init_t = self.init_t_rotation
self.X = self.X_rotation
self.x = self.x_rotation
self.C = numpy.empty(3)
self.R = numpy.empty((3,3))
self.Rinv = numpy.empty((3,3))
elif (self.deformation["type"] == "homogeneous"):
self.init_t = self.init_t_homogeneous
self.X = self.X_homogeneous
self.x = self.x_homogeneous
elif (self.deformation["type"] == "heart"):
assert (structure["type"] == "heart"), "structure type must be \"heart\" for \"heart\" type deformation. Aborting."
self.init_t = self.init_t_heart
self.X = self.X_heart
self.x = self.x_heart
self.x_inplane = numpy.empty(2)
self.X_inplane = numpy.empty(2)
self.rt = numpy.empty(2)
self.RT = numpy.empty(2)
self.L = images["L"]
self.Ri = structure["Ri"]
self.Re = structure["Re"]
self.R = numpy.empty((3,3))
else:
assert (0), "deformation type must be \"no\", \"translation\", \"rotation\", \"homogeneous\" or \"heart\". Aborting."
if (evolution["type"] == "linear"):
self.phi = self.phi_linear
elif (evolution["type"] == "sine"):
self.phi = self.phi_sine
self.T = evolution["T"]
else:
assert (0), "evolution ("+evolution["type"]+") type must be \"linear\" or \"sine\". Aborting."
def phi_linear(self, t):
return t
def phi_sine(self, t):
return math.sin(math.pi*t/self.T)**2
def init_t_no(self, t):
pass
def init_t_translation(self, t):
self.D[0] = self.deformation["Dx"] if ("Dx" in self.deformation) else 0.
self.D[1] = self.deformation["Dy"] if ("Dy" in self.deformation) else 0.
self.D[2] = self.deformation["Dz"] if ("Dz" in self.deformation) else 0.
self.D *= self.phi(t)
def init_t_rotation(self, t):
self.C[0] = self.deformation["Cx"] if ("Cx" in self.deformation) else 0.
self.C[1] = self.deformation["Cy"] if ("Cy" in self.deformation) else 0.
self.C[2] = self.deformation["Cz"] if ("Cz" in self.deformation) else 0.
Rx = self.deformation["Rx"]*math.pi/180*self.phi(t) if ("Rx" in self.deformation) else 0.
Ry = self.deformation["Ry"]*math.pi/180*self.phi(t) if ("Ry" in self.deformation) else 0.
Rz = self.deformation["Rz"]*math.pi/180*self.phi(t) if ("Rz" in self.deformation) else 0.
RRx = numpy.array([[ 1. , 0. , 0. ],
[ 0. , +math.cos(Rx), -math.sin(Rx)],
[ 0. , +math.sin(Rx), +math.cos(Rx)]])
RRy = numpy.array([[+math.cos(Ry), 0. , +math.sin(Ry)],
[ 0. , 1. , 0. ],
[-math.sin(Ry), 0. , +math.cos(Ry)]])
RRz = numpy.array([[+math.cos(Rz), -math.sin(Rz), 0. ],
[+math.sin(Rz), +math.cos(Rz), 0. ],
[ 0. , 0. , 1. ]])
self.R[:,:] = numpy.dot(numpy.dot(RRx, RRy), RRz)
self.Rinv[:,:] = numpy.linalg.inv(self.R)
def init_t_homogeneous(self, t):
if (any(E in self.deformation for E in ("Exx", "Eyy", "Ezz"))): # build F from E
Exx = self.deformation["Exx"] if ("Exx" in self.deformation) else 0.
Eyy = self.deformation["Eyy"] if ("Eyy" in self.deformation) else 0.
Ezz = self.deformation["Ezz"] if ("Ezz" in self.deformation) else 0.
self.F = numpy.array([[Exx, 0., 0.],
[ 0., Eyy, 0.],
[ 0., 0., Ezz]])*self.phi(t)
self.F *= 2
self.F += numpy.eye(3)
w, v = numpy.linalg.eig(self.F)
# assert (numpy.diag(numpy.dot(numpy.dot(numpy.transpose(v), self.F), v)) == w).all(), str(numpy.dot(numpy.dot(numpy.transpose(v), self.F), v))+" ≠ "+str(numpy.diag(w))+". Aborting."
self.F = numpy.dot(numpy.dot(v, numpy.diag(numpy.sqrt(w))), numpy.transpose(v))
else:
Fxx = self.deformation["Fxx"] if ("Fxx" in self.deformation) else 0.
Fyy = self.deformation["Fyy"] if ("Fyy" in self.deformation) else 0.
Fzz = self.deformation["Fzz"] if ("Fzz" in self.deformation) else 0.
Fxy = self.deformation["Fxy"] if ("Fxy" in self.deformation) else 0.
Fyx = self.deformation["Fyx"] if ("Fyx" in self.deformation) else 0.
Fyz = self.deformation["Fyz"] if ("Fyz" in self.deformation) else 0.
Fzy = self.deformation["Fzy"] if ("Fzy" in self.deformation) else 0.
Fzx = self.deformation["Fzx"] if ("Fzx" in self.deformation) else 0.
Fxz = self.deformation["Fxz"] if ("Fxz" in self.deformation) else 0.
self.F = numpy.eye(3) + (numpy.array([[Fxx, Fxy, Fxz],
[Fyx, Fyy, Fyz],
[Fzx, Fzy, Fzz]])-numpy.eye(3))*self.phi(t)
self.Finv = numpy.linalg.inv(self.F)
def init_t_heart(self, t):
self.dRi = self.deformation["dRi"]*self.phi(t) if ("dRi" in self.deformation) else 0.
self.dRe = self.deformation["dRi"]*self.phi(t) if ("dRi" in self.deformation) else 0.
self.dTi = self.deformation["dTi"]*self.phi(t) if ("dTi" in self.deformation) else 0.
self.dTe = self.deformation["dTe"]*self.phi(t) if ("dTe" in self.deformation) else 0.
self.A = numpy.array([[1.-(self.dRi-self.dRe)/(self.Re-self.Ri), 0.],
[ -(self.dTi-self.dTe)/(self.Re-self.Ri), 1.]])
self.Ainv = numpy.linalg.inv(self.A)
self.B = numpy.array([(1.+self.Ri/(self.Re-self.Ri))*self.dRi-self.Ri/(self.Re-self.Ri)*self.dRe,
(1.+self.Ri/(self.Re-self.Ri))*self.dTi-self.Ri/(self.Re-self.Ri)*self.dTe])
def X_no(self, x, X, Finv=None):
X[:] = x
if (Finv is not None): Finv[:,:] = numpy.identity(numpy.sqrt(numpy.size(Finv)))
def X_translation(self, x, X, Finv=None):
X[:] = x - self.D
if (Finv is not None): Finv[:,:] = numpy.identity(numpy.sqrt(numpy.size(Finv)))
def X_rotation(self, x, X, Finv=None):
X[:] = numpy.dot(self.Rinv, x - self.C) + self.C
if (Finv is not None): Finv[:,:] = self.Rinv
def X_homogeneous(self, x, X, Finv=None):
X[:] = numpy.dot(self.Finv, x)
if (Finv is not None): Finv[:,:] = self.Finv
def X_heart(self, x, X, Finv=None):
#print "x = "+str(x)
self.x_inplane[0] = x[0] - self.L[0]/2
self.x_inplane[1] = x[1] - self.L[1]/2
#print "x_inplane = "+str(self.x_inplane)
self.rt[0] = numpy.linalg.norm(self.x_inplane)
self.rt[1] = math.atan2(self.x_inplane[1], self.x_inplane[0])
#print "rt = "+str(self.rt)
self.RT[:] = numpy.dot(self.Ainv, self.rt-self.B)
#print "RT = "+str(self.RT)
X[0] = self.RT[0] * math.cos(self.RT[1]) + self.L[0]/2
X[1] = self.RT[0] * math.sin(self.RT[1]) + self.L[1]/2
X[2] = x[2]
#print "X = "+str(X)
if (Finv is not None):
Finv[0,0] = 1.+(self.dRe-self.dRi)/(self.Re-self.Ri)
Finv[0,1] = 0.
Finv[0,2] = 0.
Finv[1,0] = (self.dTe-self.dTi)/(self.Re-self.Ri)*self.rt[0]
Finv[1,1] = self.rt[0]/self.RT[0]
Finv[1,2] = 0.
Finv[2,0] = 0.
Finv[2,1] = 0.
Finv[2,2] = 1.
#print "F = "+str(Finv)
Finv[:,:] = numpy.linalg.inv(Finv)
#print "Finv = "+str(Finv)
self.R[0,0] = +math.cos(self.RT[1])
self.R[0,1] = +math.sin(self.RT[1])
self.R[0,2] = 0.
self.R[1,0] = -math.sin(self.RT[1])
self.R[1,1] = +math.cos(self.RT[1])
self.R[1,2] = 0.
self.R[2,0] = 0.
self.R[2,1] = 0.
self.R[2,2] = 1.
#print "R = "+str(self.R)
Finv[:] = numpy.dot(numpy.transpose(self.R), numpy.dot(Finv, self.R))
#print "Finv = "+str(Finv)
def x_no(self, X, x, F=None):
x[:] = X
if (F is not None): F[:,:] = numpy.identity(numpy.sqrt(numpy.size(F)))
def x_translation(self, X, x, F=None):
x[:] = X + self.D
if (F is not None): F[:,:] = numpy.identity(numpy.sqrt(numpy.size(F)))
def x_rotation(self, X, x, F=None):
x[:] = numpy.dot(self.R, X - self.C) + self.C
if (F is not None): F[:,:] = self.R
def x_homogeneous(self, X, x, F=None):
x[:] = numpy.dot(self.F, X)
if (F is not None): F[:,:] = self.F
def x_heart(self, X, x, F=None):
#print "X = "+str(X)
self.X_inplane[0] = X[0] - self.L[0]/2
self.X_inplane[1] = X[1] - self.L[1]/2
#print "X_inplane = "+str(self.X_inplane)
self.RT[0] = numpy.linalg.norm(self.X_inplane)
self.RT[1] = math.atan2(self.X_inplane[1], self.X_inplane[0])
#print "RT = "+str(self.RT)
self.rt[:] = numpy.dot(self.A, self.RT) + self.B
#print "rt = "+str(self.rt)
x[0] = self.rt[0] * math.cos(self.rt[1]) + self.L[0]/2
x[1] = self.rt[0] * math.sin(self.rt[1]) + self.L[1]/2
x[2] = X[2]
#print "x = "+str(x)
if (F is not None):
F[0,0] = 1.+(self.dRe-self.dRi)/(self.Re-self.Ri)
F[0,1] = 0.
F[0,2] = 0.
F[1,0] = (self.dTe-self.dTi)/(self.Re-self.Ri)*self.rt[0]
F[1,1] = self.rt[0]/self.RT[0]
F[1,2] = 0.
F[2,0] = 0.
F[2,1] = 0.
F[2,2] = 1.
#print "F = "+str(F)
self.R[0,0] = +math.cos(self.RT[1])
self.R[0,1] = +math.sin(self.RT[1])
self.R[0,2] = 0.
self.R[1,0] = -math.sin(self.RT[1])
self.R[1,1] = +math.cos(self.RT[1])
self.R[1,2] = 0.
self.R[2,0] = 0.
self.R[2,1] = 0.
self.R[2,2] = 1.
F[:] = numpy.dot(numpy.transpose(self.R), numpy.dot(F, self.R))
#print "F = "+str(F)
normalize_images.py 0 → 100644
+ 95
− 0
View file @ c2d3607a
#coding=utf8
################################################################################
### ###
### Created by Martin Genet, 2016-2019 ###
### ###
### École Polytechnique, Palaiseau, France ###
### ###
################################################################################
import glob
import math
import numpy
import os
import random
import vtk
import myPythonLibrary as mypy
import myVTKPythonLibrary as myvtk
import dolfin_dic as ddic
################################################################################
def normalize_images(
images_folder,
images_basename,
images_datatype,
images_ext="vti"):
images_filenames = glob.glob(images_folder+"/"+images_basename+"_[0-9]*"+"."+images_ext)
images_nframes = len(images_filenames)
images_zfill = len(images_filenames[0].rsplit("_",1)[-1].split(".",1)[0])
image_filename = images_folder+"/"+images_basename+"_"+str(0).zfill(images_zfill)+"."+images_ext
image = myvtk.readImage(
filename=image_filename,
verbose=0)
images_npoints = image.GetNumberOfPoints()
if (images_ext == "vtk"):
reader = vtk.vtkImageReader()
writer = vtk.vtkImageWriter()
elif (images_ext == "vti"):
reader = vtk.vtkXMLImageDataReader()
writer = vtk.vtkXMLImageDataWriter()
else:
assert 0, "\"ext\" must be .vtk or .vti. Aborting."
global_min = float("+Inf")
global_max = float("-Inf")
I = numpy.empty(2)
for k_frame in xrange(images_nframes):
reader.SetFileName(images_folder+"/"+images_basename+"_"+str(k_frame).zfill(images_zfill)+"."+images_ext)
reader.Update()
image_scalars = reader.GetOutput().GetPointData().GetScalars()
for k_point in xrange(images_npoints):
image_scalars.GetTuple(k_point, I)
global_min = min(global_min, I[0])
global_max = max(global_max, I[0])
print "global_min = "+str(global_min)
print "global_max = "+str(global_max)
shifter = vtk.vtkImageShiftScale()
shifter.SetInputConnection(reader.GetOutputPort())
shifter.SetShift(-global_min)
if (images_datatype in ("unsigned char", "uint8")):
shifter.SetScale(float(2**8-1)/(global_max-global_min))
shifter.SetOutputScalarTypeToUnsignedChar()
elif (images_datatype in ("unsigned short", "uint16")):
shifter.SetScale(float(2**16-1)/(global_max-global_min))
shifter.SetOutputScalarTypeToUnsignedShort()
elif (images_datatype in ("unsigned int", "uint32")):
shifter.SetScale(float(2**32-1)/(global_max-global_min))
shifter.SetOutputScalarTypeToUnsignedInt()
elif (images_datatype in ("unsigned long", "uint64")):
shifter.SetScale(float(2**64-1)/(global_max-global_min))
shifter.SetOutputScalarTypeToUnsignedLong()
elif (images_datatype in ("unsigned float", "ufloat", "float")):
shifter.SetScale(1./(global_max-global_min))
shifter.SetOutputScalarTypeToFloat()
writer.SetInputConnection(shifter.GetOutputPort())
for k_frame in xrange(images_nframes):
reader.SetFileName(images_folder+"/"+images_basename+"_"+str(k_frame).zfill(images_zfill)+"."+images_ext)
reader.Update()
shifter.Update()
writer.SetFileName(images_folder+"/"+images_basename+"_normalized"+"_"+str(k_frame).zfill(images_zfill)+"."+images_ext)
writer.Update()
writer.Write()
resample_images.py 0 → 100644
+ 151
− 0
View file @ c2d3607a
#coding=utf8
################################################################################
### ###
### Created by Martin Genet, 2016-2019 ###
### ###
### École Polytechnique, Palaiseau, France ###
### ###
################################################################################
import glob
import math
import numpy
import os
import random
import vtk
import myPythonLibrary as mypy
import myVTKPythonLibrary as myvtk
import dolfin_dic as ddic
################################################################################
def resample_images(
images_folder,
images_basename,
resampling_factors,
images_ext="vti",
write_temp_images=False):
images_filenames = glob.glob(images_folder+"/"+images_basename+"_[0-9]*"+"."+images_ext)
images_nframes = len(images_filenames)
images_zfill = len(images_filenames[0].rsplit("_",1)[-1].split(".",1)[0])
image_filename = images_folder+"/"+images_basename+"_"+str(0).zfill(images_zfill)+"."+images_ext
image = myvtk.readImage(
filename=image_filename,
verbose=0)
images_npoints = image.GetNumberOfPoints()
images_nvoxels = myvtk.getImageDimensions(
image=image,
verbose=0)
images_ndim = len(images_nvoxels)
if (images_ext == "vtk"):
reader = vtk.vtkImageReader()
writer = vtk.vtkImageWriter()
if (write_temp_images):
writer_fft = vtk.vtkImageWriter()
writer_mult = vtk.vtkImageWriter()
elif (images_ext == "vti"):
reader = vtk.vtkXMLImageDataReader()
writer = vtk.vtkXMLImageDataWriter()
if (write_temp_images):
writer_fft = vtk.vtkXMLImageDataWriter()
writer_mult = vtk.vtkXMLImageDataWriter()
else:
assert 0, "\"ext\" must be \".vtk\" or \".vti\". Aborting."
fft = vtk.vtkImageFFT()
fft.SetDimensionality(images_ndim)
fft.SetInputConnection(reader.GetOutputPort())
if (write_temp_images): writer_fft.SetInputConnection(fft.GetOutputPort())
image_filename = images_folder+"/"+images_basename+"_"+str(0).zfill(images_zfill)+"."+images_ext
mask_image = myvtk.readImage(
filename=image_filename,
verbose=0)
mask_scalars = myvtk.createDoubleArray(
name="ImageScalars",
n_components=2,
n_tuples=images_npoints,
verbose=0)
mask_image.GetPointData().SetScalars(mask_scalars)
# print mask_image.GetScalarType()
# print mask_image.GetPointData().GetScalars()
if (images_ndim == 1):
for k_point in xrange(images_npoints):
if ((k_point > images_nvoxels[0]/resampling_factors[0]/2) \
and (k_point < images_nvoxels[0] - images_nvoxels[0]/resampling_factors[0]/2)):
mask_scalars.SetTuple(k_point, [0, 0])
else:
mask_scalars.SetTuple(k_point, [1, 1])
if (images_ndim == 2):
for k_point in xrange(images_npoints):
# print "k_point = "+str(k_point)
k_y = math.floor(k_point/images_nvoxels[0])
k_x = k_point - k_y*images_nvoxels[0]
# print "k_x = "+str(k_x)
# print "k_y = "+str(k_y)
if (((k_x > images_nvoxels[0]/resampling_factors[0]/2) \
and (k_x < images_nvoxels[0] - images_nvoxels[0]/resampling_factors[0]/2)) \
or ((k_y > images_nvoxels[1]/resampling_factors[1]/2) \
and (k_y < images_nvoxels[1] - images_nvoxels[1]/resampling_factors[1]/2))):
mask_scalars.SetTuple(k_point, [0, 0])
else:
mask_scalars.SetTuple(k_point, [1, 1])
if (images_ndim == 3):
for k_point in xrange(images_npoints):
k_z = math.floor(k_point/images_nvoxels[0]/images_nvoxels[1])
k_y = math.floor((k_point - k_z*images_nvoxels[0]*images_nvoxels[1])/images_nvoxels[0])
k_x = k_point - k_z*images_nvoxels[0]*images_nvoxels[1] - k_y*images_nvoxels[0]
if (((k_x > images_nvoxels[0]/resampling_factors[0]/2) \
and (k_x < images_nvoxels[0] - images_nvoxels[0]/resampling_factors[0]/2)) \
or ((k_y > images_nvoxels[1]/resampling_factors[1]/2) \
and (k_y < images_nvoxels[1] - images_nvoxels[1]/resampling_factors[1]/2)) \
or ((k_z > images_nvoxels[2]/resampling_factors[2]/2) \
and (k_z < images_nvoxels[2] - images_nvoxels[2]/resampling_factors[2]/2))):
mask_scalars.SetTuple(k_point, [0, 0])
else:
mask_scalars.SetTuple(k_point, [1, 1])
if (write_temp_images): myvtk.writeImage(
image=mask_image,
filename=images_folder+"/"+images_basename+"_mask"+"."+images_ext,
verbose=0)
mult = vtk.vtkImageMathematics()
mult.SetOperationToMultiply()
mult.SetInputData(0, mask_image)
mult.SetInputConnection(1, fft.GetOutputPort())
if (write_temp_images): writer_mult.SetInputConnection(mult.GetOutputPort())
rfft = vtk.vtkImageRFFT()
rfft.SetDimensionality(images_ndim)
rfft.SetInputConnection(mult.GetOutputPort())
writer.SetInputConnection(rfft.GetOutputPort())
for k_frame in xrange(images_nframes):
reader.SetFileName(images_folder+"/"+images_basename+"_"+str(k_frame).zfill(images_zfill)+"."+images_ext)
reader.Update()
fft.Update()
if (write_temp_images):
writer_fft.SetFileName(images_folder+"/"+images_basename+"_fft"+"_"+str(k_frame).zfill(images_zfill)+"."+images_ext)
writer_fft.Update()
writer_fft.Write()
# print fft.GetOutput().GetScalarType()
# print fft.GetOutput().GetPointData().GetScalars()
mult.Update()
if (write_temp_images):
writer_mult.SetFileName(images_folder+"/"+images_basename+"_mult"+"_"+str(k_frame).zfill(images_zfill)+"."+images_ext)
writer_mult.Update()
writer_mult.Write()
rfft.Update()
writer.SetFileName(images_folder+"/"+images_basename+"_resampled"+"_"+str(k_frame).zfill(images_zfill)+"."+images_ext)
writer.Update()
writer.Write()
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