deeplearning/modulus/modulus-sym-v100/_modules/modulus/sym/utils/io/vtk.html
Source code for modulus.sym.utils.io.vtk
# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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"""Helper functions for generating vtk files
"""
import time
import torch
import scipy
import numpy as np
import matplotlib
import sympy as sp
import logging
import vtk
from vtk.util.numpy_support import numpy_to_vtk, vtk_to_numpy
from pathlib import Path
import pathlib
from typing import List, Dict, Union, Tuple
logger = logging.getLogger(__name__)
class VTKBase:
# Only supports working with point data
def __init__(self, file_name: str, file_dir: str):
self.file_name = file_name
self.file_dir = file_dir
self.ext = ".vtk"
self.vtk_obj = None
self.writer = None
self.export_map = {}
def save_vtk(self):
raise NotImplementedError("Implement in VTK subclass")
def get_points(self):
raise NotImplementedError("Implement in VTK subclass")
def get_cells(self):
raise NotImplementedError("Implement in VTK subclass")
def set_points(self):
raise NotImplementedError("Implement in VTK subclass")
def set_cells(self):
raise NotImplementedError("Implement in VTK subclass")
def get_array_names(self):
narrays = self.vtk_obj.GetPointData().GetNumberOfArrays()
names = []
for i in range(narrays):
names.append(self.vtk_obj.GetPointData().GetArrayName(i))
return names
def get_array(self, name: str, dim: Union[None, int] = None):
if name not in self.get_array_names():
logger.warn(f"{name} not found in data arrays")
return None
data_array = vtk_to_numpy(self.vtk_obj.GetPointData().GetArray(name))
# Expand last dim for scalars for consistency
if data_array.ndim == 1:
data_array = data_array[:, np.newaxis]
elif dim is not None:
# Get component of data array
if dim > data_array.shape[1]:
raise ValueError(
f"Dimension requested of VTK dataarray {name}:{dim} is too large. Data-array size: {data_array.shape}"
)
data_array = data_array[:, dim : dim + 1]
return data_array
def get_data_from_map(self, vtk_data_map: Dict[str, List[str]]):
data_dict = {}
coord_map = {"x": 0, "y": 1, "z": 2}
# Loop through input map values
for input_key, vtk_keys in vtk_data_map.items():
input_array = []
for vtk_key in vtk_keys:
# Check if coordinate array
if vtk_key in coord_map:
input_array0 = self.get_points(dims=[coord_map[vtk_key]])
input_array.append(input_array0)
# Check if data array
elif vtk_key.split(":")[0] in self.get_array_names():
if len(vtk_key.split(":")) > 1:
input_array0 = self.get_array(
name=vtk_key.split(":")[0], dim=int(vtk_key.split(":")[1])
)
else:
input_array0 = self.get_array(name=vtk_key)
input_array.append(input_array0)
data_dict[input_key] = np.concatenate(input_array, axis=1)
return data_dict
def var_to_vtk(
self,
data_vars: Dict[str, np.array],
file_name: str = None,
file_dir: str = None,
step: int = None,
):
if file_name is None:
file_name = self.file_name
if file_dir is None:
file_dir = self.file_dir
if step is not None:
file_name = file_name + f"{step:06}"
# Convert any non list values in input map to lists
for input_key, vtk_keys in self.export_map.items():
if isinstance(vtk_keys, str):
self.export_map[input_key] = [vtk_keys]
# Apply vtk mask, to compose multidim variables
out_var = {}
for key, data_keys in self.export_map.items():
vtk_array = []
for data_key in data_keys:
if data_key in data_vars:
if data_vars[data_key].ndim == 1:
vtk_array.append(data_vars[data_key][:, np.newaxis])
else:
vtk_array.append(data_vars[data_key])
elif data_key is None:
vtk_array.append(
np.zeros((self.vtk_obj.GetNumberOfPoints(), 1), dtype=np.short)
)
# If we recieved any data that fits the map
if len(vtk_array) > 0:
out_var[key] = np.squeeze(np.concatenate(vtk_array, axis=1))
# Add data to vtk file
# TODO: Only save points inside class and create vtk obj on save call
for key, data in out_var.items():
self.add_point_array(key, data.astype(np.float32))
self.save_vtk(file_name, file_dir)
def save_vtk(
self,
file_name: str = None,
file_dir: str = None,
compression: int = 1,
data_mode: int = 1,
):
# Compression level: 1 (worst compression, fastest) ... 9 (best compression, slowest).
# https://vtk.org/doc/nightly/html/classvtkXMLWriterBase.html
# Data mode: 0 = ascii, 1 = binary
if file_name is None:
file_name = self.file_name
if file_dir is None:
file_dir = self.file_dir
Path(file_dir).mkdir(parents=True, exist_ok=True)
file_path = Path(file_dir) / Path(file_name + self.ext)
self.writer.SetFileName(file_path)
self.writer.SetCompressorTypeToZLib()
self.writer.SetCompressionLevel(compression)
self.writer.SetDataMode(data_mode)
self.writer.SetInputData(self.vtk_obj)
self.writer.Write()
def add_point_array(self, name: str, data: np.array):
"""Adds point array data into VTK file
Parameters
----------
name : str
data array name
data : np.array
1D or 2D numpy data array
"""
assert (
data.shape[0] == self.vtk_obj.GetNumberOfPoints()
), f"Input array incorrect size. Got {data.shape[0]} instead of {self.vtk_obj.GetNumberOfPoints()}"
assert data.ndim < 3, "1D and 2D arrays supported"
data_array = numpy_to_vtk(data, deep=True)
if data.ndim == 2:
data_array.SetNumberOfComponents(data.shape[1])
data_array.SetName(name)
self.vtk_obj.GetPointData().AddArray(data_array)
def remove_point_array(self, name: str):
if name in self.get_array_names():
self.vtk_obj.GetPointData().RemoveArray(name)
else:
logger.warn(f"Point data {name} not present in VTK object")
[docs]class VTKUniformGrid(VTKBase):
"""vtkUniformGrid wrapper class
Parameters
----------
bounds : List[List[int]]
Domain bounds of each dimension
npoints : List[int]
List of number of points in each dimension
export_map : Dict[str, List[str]], optional
Export map dictionary with keys that are VTK variables names and values that are lists of output variables. Will use 1 to 1 mapping if none is provided, by default {}
file_name : str, optional
File name of output vtk file, by default "vtk_output"
file_dir : str, optional
File directory of output vtk file, by default "."
init_vtk : bool, optional
Initialize new VTK object from parameters (used by VTKFromFile), by default True
"""
def __init__(
self,
bounds: List[List[int]],
npoints: List[int],
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
init_vtk: bool = True,
):
super().__init__(file_name, file_dir)
self.vtk_obj = vtk.vtkUniformGrid()
self.writer = vtk.vtkXMLImageDataWriter()
self.ext = ".vti"
self.export_map = export_map
if init_vtk:
self.init_points(bounds, npoints)
def init_points(
self,
bounds: List[List[int]],
npoints: List[int],
):
assert len(bounds) == len(
npoints
), f"Bounds and npoints must be same length {len(bounds)}, {len(npoints)}"
assert (
len(bounds) > 0 and len(bounds) < 4
), "Only 1, 2, 3 grid dimensionality allowed"
# Padd for missing dimensions
npoints = np.array(npoints + [1, 1])
bounds = np.array(bounds + [[0, 0], [0, 0]])
dx = abs(bounds[:, 0] - bounds[:, 1]) / np.maximum(
np.ones_like(npoints), npoints - 1
)
# This is unique to uniform grid since it uses the imgdata backend
self.vtk_obj.SetOrigin(
bounds[0][0], bounds[1][0], bounds[2][0]
) # default values
self.vtk_obj.SetSpacing(dx[0], dx[1], dx[2])
self.vtk_obj.SetDimensions(npoints[0], npoints[1], npoints[2])
def get_points(self, dims: List[int] = [0, 1, 2]):
# Slow but VTK Image data does not explicitly store point coords
points = []
for i in range(self.vtk_obj.GetNumberOfPoints()):
points.append(self.vtk_obj.GetPoint(i))
points = np.array(points)
return np.concatenate([points[:, i : i + 1] for i in dims], axis=1)
def set_points(self, points: np.array):
raise NotImplementedError("Cannot set points on vtkUniformGrid")
def set_cells(self):
raise AttributeError("Cannot set the cells of a vtkStructuredPoints")
@classmethod
def init_from_obj(
cls,
vtk_obj,
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
):
vtk_wrapper = VTKUniformGrid(
None,
None,
export_map=export_map,
file_name=file_name,
file_dir=file_dir,
init_vtk=False,
)
vtk_wrapper.vtk_obj = vtk_obj
return vtk_wrapper
[docs]class VTKRectilinearGrid(VTKBase):
"""vtkRectilinearGrid wrapper class
Parameters
----------
axis_coords : List[np.array]
List of arrays that define points on each axis
export_map : Dict[str, List[str]], optional
Export map dictionary with keys that are VTK variables names and values that are lists of output variables. Will use 1 to 1 mapping if none is provided, by default {}
file_name : str, optional
File name of output vtk file, by default "vtk_output"
file_dir : str, optional
File directory of output vtk file, by default "."
init_vtk : bool, optional
Initialize new VTK object from parameters (used by VTKFromFile), by default True
"""
def __init__(
self,
axis_coords: List[np.array],
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
init_vtk: bool = True,
):
super().__init__(file_name, file_dir)
self.vtk_obj = vtk.vtkRectilinearGrid()
self.writer = vtk.vtkXMLRectilinearGridWriter()
self.ext = ".vtr"
self.export_map = export_map
if init_vtk:
self.init_points(axis_coords)
def init_points(self, coords: List[np.array]):
assert len(coords) < 4, "Maximum of 3 spacial coordinate arrays accepted"
# Padd for missing dimensions
coords = coords + [np.array([0]), np.array([0])]
# This is unique to vtkRectilinearGrid since points are not explicit
self.vtk_obj.SetDimensions(
coords[0].shape[0], coords[1].shape[0], coords[2].shape[0]
)
self.vtk_obj.SetXCoordinates(numpy_to_vtk(coords[0]))
self.vtk_obj.SetYCoordinates(numpy_to_vtk(coords[1]))
self.vtk_obj.SetZCoordinates(numpy_to_vtk(coords[2]))
def get_points(self, dims: List[int] = [0, 1, 2]):
# GetPoint in vtkRectilinearGrid takes in point container to populate since
# it does not have one internally
# https://vtk.org/doc/nightly/html/classvtkRectilinearGrid.html
points = vtk.vtkPoints()
self.vtk_obj.GetPoints(points)
# Now we can convert to numpy
points = vtk_to_numpy(points.GetData())
return np.concatenate([points[:, i : i + 1] for i in dims], axis=1)
def set_points(self, points: np.array):
raise AttributeError("Cannot set the points of a vtkRectilinearGrid explicitly")
def set_cells(self):
raise AttributeError("Cannot set the cells of a vtkRectilinearGrid explicitly")
@classmethod
def init_from_obj(
cls,
vtk_obj,
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
):
vtk_wrapper = VTKRectilinearGrid(
None,
export_map=export_map,
file_name=file_name,
file_dir=file_dir,
init_vtk=False,
)
vtk_wrapper.vtk_obj = vtk_obj
return vtk_wrapper
[docs]class VTKStructuredGrid(VTKBase):
"""vtkStructuredGrid wrapper class
Parameters
----------
points : np.array
Mesh grid of points in 'ij' format
dims : List[int]
Number of points in each dimension
export_map : Dict[str, List[str]], optional
Export map dictionary with keys that are VTK variables names and values that are lists of output variables. Will use 1 to 1 mapping if none is provided, by default {}
file_name : str, optional
File name of output vtk file, by default "vtk_output"
file_dir : str, optional
File directory of output vtk file, by default "."
init_vtk : bool, optional
Initialize new VTK object from parameters (used by VTKFromFile), by default True
"""
def __init__(
self,
points: np.array,
dims: List[int],
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
init_vtk: bool = True,
):
super().__init__(file_name, file_dir)
self.vtk_obj = vtk.vtkStructuredGrid()
self.writer = vtk.vtkXMLStructuredGridWriter()
self.ext = ".vts"
self.export_map = export_map
if init_vtk:
self.init_points(points, dims)
def init_points(self, points: np.array, dims: List[int]):
assert points.ndim == 2, "Points array must have 2 dimensions [npoints, dim]"
assert points.shape[1] < 4, "Maximum of 3 spacial point arrays accepted"
assert len(dims) == points.shape[1], "Domain dimension must match dim of points"
# Padd for missing dimensions
points = np.concatenate(
[points, np.zeros((points.shape[0], 2), dtype=np.short)], axis=1
)
dims = dims + [1, 1]
assert (
dims[0] * dims[1] * dims[2] == points.shape[0]
), "Number of points do not match provided dimensions"
pts = vtk.vtkPoints()
pts.SetNumberOfPoints(points.shape[0])
pts.SetData(numpy_to_vtk(points[:, :3]))
self.vtk_obj.SetDimensions(dims[:3])
self.vtk_obj.SetPoints(pts)
def get_points(self, dims: List[int] = [0, 1, 2]):
points = vtk_to_numpy(self.vtk_obj.GetPoints().GetData())
return np.concatenate([points[:, i : i + 1] for i in dims], axis=1)
def set_points(self, points: np.array, dims: List[int]):
points = np.concatenate(
[points, np.zeros((points.shape[0], 2), dtype=np.short)], axis=1
)
dims = dims + [1, 1]
assert (
dims[0] * dims[1] * dims[2] == points.shape[0]
), "Number of points do not match provided dimensions"
pts = vtk.vtkPoints()
pts.SetNumberOfPoints(points.shape[0])
pts.SetData(numpy_to_vtk(points[:, :3]))
self.vtk_obj.SetDimensions(dims[:3])
self.vtk_obj.SetPoints(pts)
def set_cells(self):
raise AttributeError("Cannot set the cells of a vtkStructuredGrid explicitly")
@classmethod
def init_from_obj(
cls,
vtk_obj,
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
):
vtk_wrapper = VTKStructuredGrid(
None,
None,
export_map=export_map,
file_name=file_name,
file_dir=file_dir,
init_vtk=False,
)
vtk_wrapper.vtk_obj = vtk_obj
return vtk_wrapper# ===================
# VTK Unstructured Grid
# ===================
[docs]class VTKUnstructuredGrid(VTKBase):
"""vtkUnstructuredGrid wrapper class
Parameters
----------
points : np.array
Array of point locations [npoints, (1,2 or 3)]
cell_index : Tuple[ np.array, np.array ]
Tuple of (cell_offsets, cell_connectivity) arrays.
Cell offsets is a 1D array denoting how many points make up a face for each cell.
Cell connectivity is a 1D array that contains verticies of each cell face in order
cell_types : np.array
Array of cell vtk types:
https://vtk.org/doc/nightly/html/vtkCellType_8h_source.html
export_map : Dict[str, List[str]], optional
Export map dictionary with keys that are VTK variables names and values that are lists of output variables. Will use 1 to 1 mapping if none is provided, by default {}
file_name : str, optional
File name of output vtk file, by default "vtk_output"
file_dir : str, optional
File directory of output vtk file, by default "."
init_vtk : bool, optional
Initialize new VTK object from parameters (used by VTKFromFile), by default True
"""
def __init__(
self,
points: np.array,
cell_index: Tuple[np.array, np.array],
cell_types: np.array,
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
init_vtk: bool = True,
):
super().__init__(file_name, file_dir)
self.vtk_obj = vtk.vtkUnstructuredGrid()
self.writer = vtk.vtkXMLUnstructuredGridWriter()
self.ext = ".vtu"
self.export_map = export_map
if init_vtk:
self.init_points(points, cell_index, cell_types)
def init_points(
self,
points: np.array,
cell_index: Tuple[np.array, np.array],
cell_types: np.array,
):
assert points.ndim == 2, "Points array must have 2 dimensions [npoints, dim]"
assert points.shape[1] < 4, "Maximum of 3 spacial point arrays accepted"
assert (
len(cell_index) == 2
), "Cell index must be tuple of numpy arrays containing [offsets, connectivity]"
# Could check cell type and cell index are consistent, but we assume the user
# knows what they are doing
# Padd for missing dimensions
points = np.concatenate(
[points, np.zeros((points.shape[0], 2), dtype=np.short)], axis=1
)
pts = vtk.vtkPoints()
pts.SetNumberOfPoints(points.shape[0])
pts.SetData(numpy_to_vtk(points[:, :3]))
self.vtk_obj.SetPoints(pts)
vtk_celltypes = vtk.vtkIntArray()
vtk_celltypes.SetNumberOfComponents(1)
vtk_celltypes = numpy_to_vtk(
cell_types.astype(int), array_type=vtk.vtkUnsignedCharArray().GetDataType()
)
vtk_cells = vtk.vtkCellArray()
vtk_offsets = numpy_to_vtk(
cell_index[0], array_type=vtk.vtkTypeInt64Array().GetDataType()
)
vtk_connectivity = numpy_to_vtk(
cell_index[1], array_type=vtk.vtkTypeInt64Array().GetDataType()
)
vtk_cells.SetData(vtk_offsets, vtk_connectivity)
self.vtk_obj.SetCells(vtk_celltypes, vtk_cells)
def get_points(self, dims: List[int] = [0, 1, 2]):
points = vtk_to_numpy(self.vtk_obj.GetPoints().GetData())
return np.concatenate([points[:, i : i + 1] for i in dims], axis=1)
# points = vtk_to_numpy(self.vtk_obj.GetPoints().GetData())
# points = [points[:, 0:1], points[:, 1:2], points[:, 2:3]]
# return [points[i] for i in dims]
def get_cells(self):
cells = self.vtk_obj.GetCells()
# Get cells data contains array [nedges, v1, v2, v3, ..., nedges, v1, v2, v3,...]
# Need to seperate offset and connectivity array for practical use
cell_connectivity = vtk_to_numpy(cells.GetConnectivityArray())
cell_offsets = vtk_to_numpy(cells.GetOffsetsArray())
return cell_offsets, cell_connectivity
def get_celltypes(self):
cell_types = vtk_to_numpy(self.vtk_obj.GetCellTypesArray())
return cell_types
def set_points(self, points: np.array):
assert points.ndim == 2, "Points array must have 2 dimensions [npoints, dim]"
assert points.shape[1] < 4, "Maximum of 3 spacial point arrays accepted"
points = np.concatenate(
[points, np.zeros((points.shape[0], 2), dtype=np.short)], axis=1
)
pts = vtk.vtkPoints()
pts.SetNumberOfPoints(points.shape[0])
pts.SetData(numpy_to_vtk(points[:, :3]))
self.vtk_obj.SetPoints(pts)
def set_cells(self, cell_index: Tuple[np.array, np.array], cell_types: np.array):
assert (
len(cell_index) == 2
), "Cell index must be tuple of numpy arrays containing [offsets, connectivity]"
vtk_celltypes = vtk.vtkIntArray()
vtk_celltypes.SetNumberOfComponents(1)
vtk_celltypes = numpy_to_vtk(
cell_types.astype(int), array_type=vtk.vtkUnsignedCharArray().GetDataType()
)
vtk_cells = vtk.vtkCellArray()
vtk_offsets = numpy_to_vtk(
cell_index[0], array_type=vtk.vtkTypeInt64Array().GetDataType()
)
vtk_connectivity = numpy_to_vtk(
cell_index[1], array_type=vtk.vtkTypeInt64Array().GetDataType()
)
vtk_cells.SetData(vtk_offsets, vtk_connectivity)
self.vtk_obj.SetCells(vtk_celltypes, vtk_cells)
@classmethod
def init_from_obj(
cls,
vtk_obj,
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
):
vtk_wrapper = VTKUnstructuredGrid(
None,
None,
None,
export_map=export_map,
file_name=file_name,
file_dir=file_dir,
init_vtk=False,
)
vtk_wrapper.vtk_obj = vtk_obj
return vtk_wrapper# ===================
# VTK Polydata
# ===================
[docs]class VTKPolyData(VTKBase):
"""vtkPolyData wrapper class
Parameters
----------
points : np.array
Array of point locations [npoints, (1,2 or 3)]
line_index : np.array, optional
Array of line connections [nedges, 2], by default None
poly_index : Tuple[poly_offsets, poly_connectivity]
Tuple of polygon offsets and polygon connectivity arrays.
Polygon offsets is a 1D array denoting how many points make up a face for each polygon.
Polygon connectivity is a 1D array that contains verticies of each polygon face in order, by default None
export_map : Dict[str, List[str]], optional
Export map dictionary with keys that are VTK variables names and values that are lists of output variables. Will use 1 to 1 mapping if none is provided, by default {}
file_name : str, optional
File name of output vtk file, by default "vtk_output"
file_dir : str, optional
File directory of output vtk file, by default "."
init_vtk : bool, optional
Initialize new VTK object from parameters (used by VTKFromFile), by default True
"""
def __init__(
self,
points: np.array,
line_index: np.array = None,
poly_index: Tuple[
np.array, np.array
] = None, # Tuple[poly_offsets, poly_connectivity]
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
init_vtk: bool = True,
):
super().__init__(file_name, file_dir)
self.vtk_obj = vtk.vtkPolyData()
self.writer = vtk.vtkXMLPolyDataWriter()
self.ext = ".vtp"
self.export_map = export_map
if init_vtk:
self.init_points(points, line_index, poly_index)
def init_points(
self,
points: np.array,
line_index: np.array = None,
poly_index: Tuple[np.array, np.array] = None,
):
assert points.ndim == 2, "Points array must have 2 dimensions [npoints, dim]"
assert points.shape[1] < 4, "Maximum of 3 spacial point arrays accepted"
# Padd for missing dimensions
points = np.concatenate(
[points, np.zeros((points.shape[0], 2), dtype=np.short)], axis=1
)
pts = vtk.vtkPoints()
pts.SetNumberOfPoints(int(points.shape[0]))
pts.SetData(numpy_to_vtk(points[:, :3]))
self.vtk_obj.SetPoints(pts)
# Add cell array for verts
vert_cells = vtk.vtkCellArray()
for i in range(points.shape[0]):
vert_cells.InsertNextCell(1)
vert_cells.InsertCellPoint(i)
self.vtk_obj.SetVerts(vert_cells)
if line_index is not None:
self.set_lines(line_index)
if poly_index is not None:
self.set_polys(poly_index)
def get_points(self, dims: List[int] = [0, 1, 2]):
points = vtk_to_numpy(self.vtk_obj.GetPoints().GetData())
return np.concatenate([points[:, i : i + 1] for i in dims], axis=1)
def get_lines(self):
lines = vtk_to_numpy(self.vtk_obj.GetLines().GetData())
line_index = np.stack([lines[1::3], lines[2::3]], axis=1)
return line_index
def get_polys(self):
polys = self.vtk_obj.GetPolys()
# Poly data contains array [nedges, v1, v2, v3, ..., nedges, v1, v2, v3,...]
# Need to seperate offset and connectivity array for practical use
poly_connectivity = vtk_to_numpy(polys.GetConnectivityArray())
poly_offsets = vtk_to_numpy(polys.GetOffsetsArray())
return poly_offsets, poly_connectivity
def get_cells(self):
raise AttributeError("vtkPolyData has polys not cells, call get_polys instead")
def set_points(self, points: np.array):
assert points.ndim == 2, "Points array must have 2 dimensions [npoints, dim]"
assert points.shape[1] < 4, "Maximum of 3 spacial point arrays accepted"
points = np.concatenate(
[points, np.zeros((points.shape[0], 2), dtype=np.short)], axis=1
)
pts = vtk.vtkPoints()
pts.SetNumberOfPoints(points.shape[0])
pts.SetData(numpy_to_vtk(points[:, :3]))
self.vtk_obj.SetPoints(pts)
# Add cell array for verts
vert_cells = vtk.vtkCellArray()
for i in range(points.shape[0]):
vert_cells.InsertNextCell(1)
vert_cells.InsertCellPoint(i)
self.vtk_obj.SetVerts(vert_cells)
def set_lines(self, edge_index: np.array):
assert (
edge_index.ndim == 2 and edge_index.shape[1] == 2
), "Edge index array must have 2 dimensions [npoints, 2]"
lines = vtk.vtkCellArray()
for i in range(edge_index.shape[0]):
lines.InsertNextCell(2)
lines.InsertCellPoint(edge_index[i, 0])
lines.InsertCellPoint(edge_index[i, 1])
self.vtk_obj.SetLines(lines)
def set_polys(self, poly_index: Tuple[np.array, np.array]):
assert (
len(poly_index) == 2
), "poly_index should be tuple of (poly_offsets, poly_connectivity)"
vtk_polys = vtk.vtkCellArray()
vtk_offsets = numpy_to_vtk(
poly_index[0], array_type=vtk.vtkTypeInt64Array().GetDataType()
)
vtk_connectivity = numpy_to_vtk(
poly_index[1], array_type=vtk.vtkTypeInt64Array().GetDataType()
)
vtk_polys.SetData(vtk_offsets, vtk_connectivity)
self.vtk_obj.SetPolys(vtk_polys)
def set_cells(self):
raise AttributeError("vtkPolyData has polys not cells, call set_polys instead")
@classmethod
def init_from_obj(
cls,
vtk_obj,
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
):
vtk_wrapper = VTKPolyData(
None,
export_map=export_map,
file_name=file_name,
file_dir=file_dir,
init_vtk=False,
)
vtk_wrapper.vtk_obj = vtk_obj
return vtk_wrapper
[docs]class VTKFromFile(object):
"""Reads VTK file into memory and constructs corresponding VTK object
Parameters
----------
file_path : str
File directory/name of input vtk file
export_map : Dict[str, List[str]], optional
Export map dictionary with keys that are VTK variables names and values that are lists of output variables. Will use 1 to 1 mapping if none is provided, by default {}
file_name : str, optional
File name of output vtk file, by default "vtk_output"
file_dir : str, optional
File directory of output vtk file, by default "."
force_legacy : bool, optional
Force a legacy only read, by default False
"""
def __new__(
cls,
file_path: str,
export_map: Dict[str, List[str]] = {},
file_name: str = "vtk_output",
file_dir: str = ".",
force_legacy: bool = False,
) -> None:
assert Path(file_path).is_file(), f"Provided VTK file {file_path} not found"
read_success = False
# Attempt to create XML reader
if not force_legacy:
try:
vtk_reader = cls.readXMLVTK(file_path)
read_success = True
except:
logger.warn("VTK file not valid XML format, will attempt legacy load")
# If failed or legacy force, create VTK Reader
if not read_success:
try:
vtk_reader = cls.readLegacyVTK(file_path)
read_success = True
except:
logger.warn("VTK file not valid VTK format")
# Hopefully VTK reader is loaded
assert read_success, "Failed to load VTK file in either XML or Legacy format"
logger.info(f"Read {Path(file_path).name} file successfully")
return cls.extractVTKObject(
vtk_reader=vtk_reader,
export_map=export_map,
file_name=file_name,
file_dir=file_dir,
)
@classmethod
def extractVTKObject(cls, vtk_reader, **kwargs) -> VTKBase:
# Get vtk object from reader
vtk_obj = vtk_reader.GetOutput()
# Create modulus.sym.VTK wrapper
if vtk_obj.__vtkname__ == "vtkImageData":
vtk_wrapper = VTKUniformGrid.init_from_obj(vtk_obj, **kwargs)
elif vtk_obj.__vtkname__ == "vtkRectilinearGrid":
vtk_wrapper = VTKRectilinearGrid.init_from_obj(vtk_obj, **kwargs)
elif vtk_obj.__vtkname__ == "vtkStructuredGrid":
vtk_wrapper = VTKStructuredGrid.init_from_obj(vtk_obj, **kwargs)
elif vtk_obj.__vtkname__ == "vtkUnstructuredGrid":
vtk_wrapper = VTKUnstructuredGrid.init_from_obj(vtk_obj, **kwargs)
elif vtk_obj.__vtkname__ == "vtkPolyData":
vtk_wrapper = VTKPolyData.init_from_obj(vtk_obj, **kwargs)
else:
raise ValueError("Unsupported vtk data type read")
logger.info(f"Loaded {vtk_obj.__vtkname__} object from file")
return vtk_wrapper
@classmethod
def readXMLVTK(cls, file_path: str):
# vtk.vtkXMLGenericDataObjectReader does not seem to work
# Could read first like of XML and check VTKFile type=...
file_path = Path(file_path)
if file_path.suffix == ".vti":
vtk_reader = vtk.vtkXMLImageDataReader()
elif file_path.suffix == ".vtr":
vtk_reader = vtk.vtkXMLRectilinearGridReader()
elif file_path.suffix == ".vts":
vtk_reader = vtk.vtkXMLStructuredGridReader()
elif file_path.suffix == ".vtu":
vtk_reader = vtk.vtkXMLUnstructuredGridReader()
elif file_path.suffix == ".vtp":
vtk_reader = vtk.vtkXMLPolyDataReader()
else:
raise ValueError("Unsupported XML VTK format")
vtk_reader.SetFileName(file_path)
vtk_reader.Update()
return vtk_reader
@classmethod
def readLegacyVTK(cls, file_path: str):
vtk_reader = vtk.vtkGenericDataObjectReader()
vtk_reader.SetFileName(file_path)
vtk_reader.ReadAllScalarsOn()
vtk_reader.ReadAllVectorsOn()
vtk_reader.Update()
return vtk_reader
[docs]def var_to_polyvtk(
var_dict: Dict[str, np.array], file_path: str, coordinates=["x", "y", "z"]
):
"""Helper method for nodes to export thier variables to a vtkPolyData file
Should be avoided when possible as other VTK formats can save on memory.
Parameters
----------
var_dict : Dict[str, np.array]
Dictionary of variables in the array format [nstates, dim]
file_path : str
File directory/name of output vtk file
coordinates : list, optional
Variable names that corresponds to point positions, by default ["x", "y", "z"]
"""
# Extract point locations
points = []
for axis in coordinates:
if axis not in var_dict.keys():
data0 = next(iter(var_dict.values()))
points.append(np.zeros((data0.shape[0], 1), dtype=np.short))
else:
points.append(var_dict[axis])
del var_dict[axis]
points = np.concatenate(points, axis=1)
# Create 1:1 export map
export_map = {}
for key in var_dict.keys():
export_map[key] = [key]
file_path = Path(file_path)
vtk_obj = VTKPolyData(
points=points,
export_map=export_map,
file_name=file_path.stem,
file_dir=file_path.parents[0],
)
vtk_obj.var_to_vtk(data_vars=var_dict)
[docs]def grid_to_vtk(var_dict: Dict[str, np.array], file_path: str, batch_index: int = 0):
"""Helper method for nodes to export image/grid data to vtkUniformData file.
Arrays should be in the numpy 'ij' layout (element [0,0] is origin)
Parameters
----------
var_dict : Dict[str, np.array]
Dictionary of variables in the array format [batch, dim, xdim, ydim, zdim]
file_path : str
File directory/name of output vtk file
batch_index : int, optional
Batch index to write to file, by default 0
"""
# convert keys to strings
var = {str(key): value for key, value in var_dict.items()}
shape = np.shape(next(iter(var.values())))
assert len(shape) > 2 and len(shape) < 6, "Input variables must be dim 3, 4, 5"
# Padd for any missing dims
bsize = shape[0]
cdim = shape[1]
grid_shape = list(shape[2:])
bounds = [[0, i - 1] for i in grid_shape]
# Flatten data and select batch
shaped_dict = {}
for key in var_dict.keys():
shaped_dict[key] = var_dict[key][batch_index]
cdim = shaped_dict[key].shape[0]
shaped_dict[key] = shaped_dict[key].reshape(cdim, -1).T
# Create 1:1 export map
export_map = {}
for key in shaped_dict.keys():
export_map[key] = [key]
file_path = Path(file_path)
vtk_obj = VTKUniformGrid(
bounds=bounds,
npoints=grid_shape,
export_map=export_map,
file_name=file_path.stem,
file_dir=file_path.parents[0],
)
vtk_obj.var_to_vtk(data_vars=shaped_dict)