def brains(sim):
sim.dim = 2
sim.sigma = .5
sim.sfactor = 1./numpy.power(sim.sigma, 2)
sim.num_points = (90,110)
sim.domain_max = None
sim.dx = (1.,1.)
sim.num_times = 11
sim.time_min = 0.
sim.time_max = 1.
sim.cg_init_eps = 1e-3
sim.write_iter = file_write_iter
brain_image_dir = os.environ["HOME"] + "/IMAGES/meta_images/child/"
sim.kvn = 'laplacian'
sim.khn = 'laplacian'
sim.kvs = 3.
sim.khs = .1
sim.kvo = 4
sim.kho = 4
logging.info("KV params: name=%s, sigma=%f, order=%f" \
% (sim.kvn,sim.kvs,sim.kvo))
logging.info("KH params: name=%s, sigma=%f, order=%f" \
% (sim.khn,sim.khs,sim.kho))
num_nodes = 90*110
sim.sc = diffeomorphisms.gridScalars()
sim.sc.loadAnalyze(brain_image_dir + "child_2d.hdr")
#sim.template_in = sim.sc.data[45,...].reshape(num_nodes)
sim.target_in = sim.sc.data.reshape(num_nodes)
sim.sc = diffeomorphisms.gridScalars()
sim.sc.loadAnalyze(brain_image_dir + "adult_2d.hdr")
#sim.target_in = sim.sc.data[45,...].reshape(num_nodes)
sim.template_in = sim.sc.data.reshape(num_nodes)
def lung_downsample(sim):
sim.dim = 3
sim.num_target_times = 5
sim.num_times_disc = 10
sim.num_times = sim.num_times_disc * sim.num_target_times + 1
sim.times = numpy.linspace(0, 1, sim.num_times)
sim.dt = 1.0 / (sim.num_times - 1)
sim.sigma = 0.1
sim.num_points_data = numpy.array([256, 184, 160])
sim.mults = numpy.array([2, 2, 2]).astype(int)
sim.num_points = (sim.num_points_data / sim.mults).astype(int)
sim.dx_data = (1.0, 1.0, 1.0)
sim.domain_max_data = None
sim.dx = None # (1.,1.,1.)
sim.domain_max = numpy.array([128.0, 92.0, 80.0])
sim.gradEps = 1e-8
sim.rg = regularGrid.RegularGrid(
sim.dim, num_points=sim.num_points, domain_max=sim.domain_max, dx=sim.dx, mesh_name="lddmm"
)
sim.rg_data = regularGrid.RegularGrid(
sim.dim, num_points=sim.num_points_data, domain_max=sim.domain_max_data, dx=sim.dx_data, mesh_name="lddmm_data"
)
sim.I = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.I_interp = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.p = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sc = diffeomorphisms.gridScalars()
sc.loadAnalyze(lung_image_dir + "test007.hdr")
sim.I[:, 0.0 * sim.num_times_disc] = sim.apply_sync_filter(sc.data.reshape(sim.rg_data.num_nodes), sim.mults)
sc.loadAnalyze(lung_image_dir + "test009.hdr")
sim.I[:, 1.0 * sim.num_times_disc] = sim.apply_sync_filter(sc.data.reshape(sim.rg_data.num_nodes), sim.mults)
sc.loadAnalyze(lung_image_dir + "test011.hdr")
sim.I[:, 2.0 * sim.num_times_disc] = sim.apply_sync_filter(sc.data.reshape(sim.rg_data.num_nodes), sim.mults)
sc.loadAnalyze(lung_image_dir + "test013.hdr")
sim.I[:, 3.0 * sim.num_times_disc] = sim.apply_sync_filter(sc.data.reshape(sim.rg_data.num_nodes), sim.mults)
sc.loadAnalyze(lung_image_dir + "test015.hdr")
sim.I[:, 4.0 * sim.num_times_disc] = sim.apply_sync_filter(sc.data.reshape(sim.rg_data.num_nodes), sim.mults)
sim.I /= 255.0
for t in range(sim.num_target_times):
sim.rg.create_vtk_sg()
sim.rg.add_vtk_point_data(sim.I[:, t * sim.num_times_disc], "I")
sim.rg.vtk_write(t, "targets", output_dir=sim.output_dir)
sim.pool_size = multiproc_pool_size
sim.pool_timeout = multiproc_pool_timeout
sim.write_iter = file_write_iter
sim.verbose_file_output = False
logging.info("lung data image parameters: ")
logging.info("dimension: %d" % (sim.dim))
logging.info("num_points: %s" % (str(sim.rg.num_points)))
logging.info("domain_max: %s" % (str(sim.rg.domain_max)))
logging.info("dx: %s" % (str(sim.rg.dx)))
logging.info("sigma: %f" % (sim.sigma))
logging.info("dt: %f" % (sim.dt))
def lung(sim):
sim.dim = 3
sim.num_target_times = 4
sim.num_times_disc = 10
sim.num_times = sim.num_times_disc * sim.num_target_times + 1
sim.times = numpy.linspace(0, 1, sim.num_times)
sim.dt = 1.0 / (sim.num_times - 1)
sim.sigma = 1.0
sim.alpha = 7.0 # 5.
sim.gamma = 1.0
sim.Lpower = 2.0
sim.num_points = numpy.array([256, 190, 160])
sim.dx = numpy.array([1.0, 1.0, 1.0])
sim.domain_max = None
sim.cg_init_eps = 1e-3
sim.rg = regularGrid.RegularGrid(
sim.dim, num_points=sim.num_points, domain_max=sim.domain_max, dx=sim.dx, mesh_name="lddmm"
)
sim.I = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.I_interp = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.p = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.sc = diffeomorphisms.gridScalars()
sim.sc.loadAnalyze(lung_image_dir + "ic007.hdr")
sim.I[:, 0.0 * sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes)
sim.sc.loadAnalyze(lung_image_dir + "ic009.hdr")
sim.I[:, 1.0 * sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes)
sim.sc.loadAnalyze(lung_image_dir + "ic011.hdr")
sim.I[:, 2.0 * sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes)
sim.sc.loadAnalyze(lung_image_dir + "ic013.hdr")
sim.I[:, 3.0 * sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes)
sim.sc.loadAnalyze(lung_image_dir + "ic015.hdr")
sim.I[:, 4.0 * sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes)
for t in range(sim.num_target_times):
sim.rg.create_vtk_sg()
sim.rg.add_vtk_point_data(sim.I[:, t * sim.num_times_disc], "I")
sim.rg.vtk_write(t, "targets", output_dir=sim.output_dir)
sim.pool_size = multiproc_pool_size
sim.pool_timeout = multiproc_pool_timeout
sim.write_iter = file_write_iter
sim.verbose_file_output = False
logging.info("lung data image parameters: ")
logging.info("dimension: %d" % (sim.dim))
logging.info("num_points: %s" % (str(sim.rg.num_points)))
logging.info("domain_max: %s" % (str(sim.rg.domain_max)))
logging.info("dx: %s" % (str(sim.rg.dx)))
logging.info("sigma: %f" % (sim.sigma))
logging.info("dt: %f" % (sim.dt))
logging.info("kernel params- alpha: %f, gamma: %f, Lpower: %f" % (sim.alpha, sim.gamma, sim.Lpower))
def biocard(sim):
sim.dim = 3
sim.num_target_times = 1
sim.num_times_disc = 10
sim.num_times = sim.num_times_disc * sim.num_target_times + 1
sim.times = numpy.linspace(0, 1, sim.num_times)
sim.dt = 1.0 / (sim.num_times - 1)
sim.sigma = 1.0 / 255.0
sim.alpha = 0.01
sim.gamma = 1.0
sim.Lpower = 2.0
sim.num_points = numpy.array([40, 32, 40])
sim.dx = numpy.array([0.9375, 2.0, 0.9375])
sim.domain_max = None
sim.cg_init_eps = 1e-3
sim.rg = regularGrid.RegularGrid(
sim.dim, num_points=sim.num_points, domain_max=sim.domain_max, dx=sim.dx, mesh_name="lddmm"
)
sim.I = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.I_interp = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.p = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.sc = diffeomorphisms.gridScalars()
sim.sc.loadAnalyze(biocard_image_dir + "regR2_cut.hdr")
sim.I[:, 0.0 * sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes).copy()
sim.sc.loadAnalyze(biocard_image_dir + "regR3_cut.hdr")
sim.I[:, 1.0 * sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes).copy()
# sim.sc.loadAnalyze(biocard_image_dir + "regR4_cut.hdr")
# sim.I[:,2.*sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes)
# sim.sc.loadAnalyze(biocard_image_dir + "regR5_cut.hdr")
# sim.I[:,3.*sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes)
sim.pool_size = multiproc_pool_size
sim.pool_timeout = multiproc_pool_timeout
sim.write_iter = file_write_iter
sim.verbose_file_output = False
logging.info("Biocard image parameters: ")
logging.info("dimension: %d" % (sim.dim))
logging.info("num_points: %s" % (str(sim.rg.num_points)))
logging.info("domain_max: %s" % (str(sim.rg.domain_max)))
logging.info("dx: %s" % (str(sim.rg.dx)))
logging.info("sigma: %f" % (sim.sigma))
logging.info("dt: %f" % (sim.dt))
logging.info("kernel params- alpha: %f, gamma: %f, Lpower: %f" % (sim.alpha, sim.gamma, sim.Lpower))
def monkey(sim):
sim.dim = 2
sim.num_target_times = 1
sim.num_times_disc = 10
sim.num_times = sim.num_times_disc * sim.num_target_times + 1
sim.times = numpy.linspace(0, 1, sim.num_times)
sim.dt = 1.0 / (sim.num_times - 1)
sim.sigma = 1.0
sim.alpha = 0.002
sim.gamma = 1.0
sim.Lpower = 2.0
sim.num_points = numpy.array([80, 80])
sim.domain_max = numpy.array([0.5, 0.5])
# sim.dx = numpy.array([1.,1.,1.])
sim.dx = None
sim.rg = regularGrid.RegularGrid(
sim.dim, num_points=sim.num_points, domain_max=sim.domain_max, dx=sim.dx, mesh_name="lddmm"
)
sim.I = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.I_interp = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.p = numpy.zeros((sim.rg.num_nodes, sim.num_times))
sim.sc = diffeomorphisms.gridScalars()
sim.sc.loadAnalyze("/cis/home/clr/cawork/monkey/monkey1_80_80.hdr")
sim.I[:, 0.0 * sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes)
sim.sc.loadAnalyze("/cis/home/clr/cawork/monkey/monkey2_80_80.hdr")
sim.I[:, 1.0 * sim.num_times_disc] = sim.sc.data.reshape(sim.rg.num_nodes)
for t in range(sim.num_target_times):
sim.rg.create_vtk_sg()
sim.rg.add_vtk_point_data(sim.I[:, t * sim.num_times_disc], "I")
sim.rg.vtk_write(t, "targets", output_dir=sim.output_dir)
logging.info("monkey data image parameters: ")
logging.info("dimension: %d" % (sim.dim))
logging.info("num_points: %s" % (str(sim.rg.num_points)))
logging.info("domain_max: %s" % (str(sim.rg.domain_max)))
logging.info("dx: %s" % (str(sim.rg.dx)))
logging.info("sigma: %f" % (sim.sigma))
logging.info("dt: %f" % (sim.dt))
