def generate(self, params):
if self.settings['moving']:
for_pos = params['for_pos']
else:
for_pos = np.zeros((3,))
nx = np.abs(int((self.x1-self.x0)/self.dx + 1))
ny = np.abs(int((self.y1-self.y0)/self.dy + 1))
nz = np.abs(int((self.z1-self.z0)/self.dz + 1))
xarray = np.linspace(self.x0, self.x1, nx) + for_pos[0]
yarray = np.linspace(self.y0, self.y1, ny) + for_pos[1]
zarray = np.linspace(self.z0, self.z1, nz) + for_pos[2]
grid = []
for iz in range(nz):
grid.append(np.zeros((3, nx, ny), dtype=ct.c_double))
for ix in range(nx):
for iy in range(ny):
grid[iz][0, ix, iy] = xarray[ix]
grid[iz][1, ix, iy] = yarray[iy]
grid[iz][2, ix, iy] = zarray[iz]
vtk_info = tvtk.RectilinearGrid()
vtk_info.dimensions = np.array([nx, ny, nz], dtype=int)
vtk_info.x_coordinates = xarray
vtk_info.y_coordinates = yarray
vtk_info.z_coordinates = zarray
return vtk_info, grid
def rectilinear_grid():
data = random.random((3, 3, 3))
r = tvtk.RectilinearGrid()
r.point_data.scalars = data.ravel()
r.point_data.scalars.name = 'scalars'
r.dimensions = data.shape
r.x_coordinates = array((0, 0.7, 1.4))
r.y_coordinates = array((0, 1, 3))
r.z_coordinates = array((0, .5, 2))
return r
def setUp(self):
datasets = [tvtk.ImageData(),
tvtk.StructuredPoints(),
tvtk.RectilinearGrid(),
tvtk.StructuredGrid(),
tvtk.PolyData(),
tvtk.UnstructuredGrid(),
]
exts = ['.vti', '.vti', '.vtr', '.vts', '.vtp', '.vtu']
self.datasets = datasets
self.exts = exts
def test5(self):
# imageData数据类型
img = tvtk.ImageData(spacing=(1, 1, 1),
origin=(0, 0, 0),
dimensions=(3, 4, 5))
#RectilinearGrid数据类型
x = np.array([0, 3, 5, 6])
y = np.array([3, 5, 9, 12])
z = np.array([4, 5, 7, 9])
r = tvtk.RectilinearGrid()
r.x_coordinates = x
r.y_coordinates = y
r.z_coordinates = z
r.dimensions = len(x), len(y), len(z)
for i in range(64):
print(r.get_point(i))
def test_tvtk_dataset_name(self):
"Can tvtk datasets can be converted to names correctly."
datasets = [
tvtk.ImageData(),
tvtk.StructuredPoints(),
tvtk.RectilinearGrid(),
tvtk.StructuredGrid(),
tvtk.PolyData(),
tvtk.UnstructuredGrid(),
tvtk.Property(), # Not a dataset!
'foo', # Not a TVTK object.
]
expect = [
'image_data', 'image_data', 'rectilinear_grid', 'structured_grid',
'poly_data', 'unstructured_grid', 'none', 'none'
]
result = [pipeline_info.get_tvtk_dataset_name(d) for d in datasets]
self.assertEqual(result, expect)
def _mk_rectilinear_grid(self):
""" Creates a RectilinearGrid VTK data set using the factory's
attributes.
"""
rg = tvtk.RectilinearGrid()
x = self.position_x.squeeze()
if x.ndim == 3:
x = x[:, 0, 0]
y = self.position_y.squeeze()
if y.ndim == 3:
y = y[0, :, 0]
z = self.position_z.squeeze()
if z.ndim == 3:
z = z[0, 0, :]
# FIXME: We should check array size here.
rg.dimensions = (x.size, y.size, z.size)
rg.x_coordinates = x
rg.y_coordinates = y
rg.z_coordinates = z
self._vtk_source = rg
self._mayavi_source = VTKDataSource(data=self._vtk_source)
def main():
parser = argparse.ArgumentParser(description='Convert 3D data to VTK.')
parser.add_argument('input', help='input file')
parser.add_argument('output', help='output file')
args = parser.parse_args()
jd, d = load_bin(args.input)
b = jd['bbox']
s = jd['size']
x = np.linspace(b[0], b[1], s[0])
y = np.linspace(b[2], b[3], s[1])
z = np.linspace(b[4], b[5], s[2])
hx = x[1] - x[0]
hy = y[1] - y[0]
hz = z[1] - z[0]
n = [s[0] - 1, s[1] - 1, s[2] - 1]
newx = np.linspace(b[0] + hx / 2, b[1] - hx / 2, n[0])
newy = np.linspace(b[2] + hy / 2, b[3] - hy / 2, n[1])
newz = np.linspace(b[4] + hz / 2, b[5] - hz / 2, n[2])
f = RegularGridInterpolator(points=(z, y, x), values=d, fill_value=None)
zv, yv, xv = np.meshgrid(newz, newy, newx, indexing='ij')
data = f((zv.ravel(), yv.ravel(), xv.ravel()))
#grid = tvtk.ImageData(spacing=(hx, hy, hz), origin=(b[0], b[2], b[4]), dimensions=s)
grid = tvtk.RectilinearGrid(dimensions=s)
grid.x_coordinates = x
grid.y_coordinates = y
grid.z_coordinates = z
grid.cell_data.scalars = np.ravel(data, order='F')
grid.cell_data.scalars.name = 'data'
# Writes legacy ".vtk" format if filename ends with "vtk", otherwise
# this will write data using the newer xml-based format.
write_data(grid, args.output)
from tvtk.api import tvtk
import numpy as np
print("\n----------------------ImageData----------------------")
img = tvtk.ImageData(
# origin: 三维网格数据的起点坐标
# spacing: 三维数据再X、Y、Z上点的间距
# dimensions：X、Y、Z上的网格数
spacing=(1, 1, 1),
origin=(1, 2, 3),
dimensions=(3, 4, 5))
print(img.get_point(0))
print("前6个点坐标\n")
for n in range(6):
print("%.1f, %.1f, %.1f" % img.get_point(n))
print("\n----------------------RectilinearGrid----------------------")
x = np.array([0, 3, 9, 15])
y = np.array([0, 1, 5])
z = np.array([0, 2, 3])
r = tvtk.RectilinearGrid()
r.x_coordinates = x
r.y_coordinates = y
r.z_coordinates = z
r.dimensions = len(x), len(y), len(z)
print("前6个点坐标\n")
for n in range(6):
print(r.get_point(n))
