mirror of
https://github.com/JuliaFEM/JuliaFEM.jl.git
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Jukka Aho
427 lines
11 KiB
Plaintext
427 lines
11 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Exporting data to Xdmf format\n",
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"\n",
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"Author(s): Jukka Aho <jukka.aho@kapsi.fi>\n",
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"\n",
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"Python example how to export data to Xdmf format using Python"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import sys\n",
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"import os\n",
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"sys.path.append(os.path.expanduser('~/opt/xdmf/lib/python'))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"from Xdmf import *"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Export mesh"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"grid = XdmfUnstructuredGrid.New()\n",
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"grid.setTime(XdmfTime.New(123))\n",
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"geometry = XdmfGeometry.New()\n",
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"topology = XdmfTopology.New()\n",
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"geometry.setType(XdmfGeometryType.XYZ())\n",
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"topology.setType(XdmfTopologyType.Mixed())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([[ 0., 0., 0.],\n",
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" [ 1., 0., 0.],\n",
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" [ 0., 1., 0.],\n",
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" [ 0., 0., 1.]])"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import numpy as np\n",
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"# one linear tetra\n",
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"nodes = np.array([[0.0, 0.0, 0.0], [1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]])\n",
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"nodes"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"It needs to be in 1d list:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"list(nodes.flatten())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"geometry.insertAsFloat32(0, list(nodes.flatten()))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Topology; connect nodes 1 - 4 to form tetra\n",
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"\n",
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"List is here:\n",
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"\n",
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"http://public.kiteware.com/pipermail/2013-July/028859.html"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"topology.insertAsInt32(0, [0x6, 1, 2, 3, 4]) # Not sure starts this from 0 or 1"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**update**, node numbering starts from 0."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"grid.setGeometry(geometry)\n",
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"grid.setTopology(topology)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Export fields"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Give scalar value to cells (i.e. elements)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"temperature = XdmfAttribute.New()\n",
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"temperature.setType(XdmfAttributeType.Scalar())\n",
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"temperature.setCenter(XdmfAttributeCenter.Cell())\n",
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"temperature.setName(\"Temperature field\")\n",
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"temperature.insertAsInt32(0, [56])\n",
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"grid.insert(temperature)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Give vector values to nodes"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"density = XdmfAttribute.New()\n",
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"density.setType(XdmfAttributeType.Vector())\n",
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"density.setCenter(XdmfAttributeCenter.Node())\n",
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"density.setName(\"Density\")\n",
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"density.insertAsFloat32(0, [1.3, 2.4, 4.5, 6.7])\n",
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"grid.insert(density)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Write to file"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"I think this is not mandatory but create temporal collection anyway:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"coll = XdmfGridCollection.New()\n",
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"coll.setType(XdmfGridCollectionType.Temporal())\n",
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"coll.insert(grid)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Create domain and write to disk"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"domain = XdmfDomain.New()\n",
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"domain.insert(coll)\n",
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"writer = XdmfWriter.New(\"testdata.xmf\")\n",
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"domain.accept(writer)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"testdata.h5 testdata.xmf\r\n"
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]
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}
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],
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"source": [
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"!ls testdata*"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"<?xml version=\"1.0\" encoding=\"utf-8\"?>\r\n",
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"<Xdmf xmlns:xi=\"http://www.w3.org/2001/XInclude\" Version=\"2.1\">\r\n",
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" <Domain>\r\n",
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" <Grid CollectionType=\"Temporal\" GridType=\"Collection\" Name=\"Collection\">\r\n",
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" <Geometry Type=\"None\"/>\r\n",
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" <Topology Dimensions=\"0\" Type=\"NoTopology\"/>\r\n",
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" <Grid Name=\"Grid\">\r\n",
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" <Time Value=\"123\"/>\r\n",
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" <Geometry Type=\"XYZ\">\r\n",
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" <DataItem DataType=\"Float\" Dimensions=\"12\" Format=\"XML\" Precision=\"4\">0 0 0 1 0 0 0 1 0 0 0 1</DataItem>\r\n",
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" </Geometry>\r\n",
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" <Topology Dimensions=\"1\" Type=\"Mixed\">\r\n",
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" <DataItem DataType=\"Int\" Dimensions=\"5\" Format=\"XML\" Precision=\"4\">6 1 2 3 4</DataItem>\r\n",
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" </Topology>\r\n",
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" <Attribute Center=\"Cell\" Name=\"Temperature field\" Type=\"Scalar\">\r\n",
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" <DataItem DataType=\"Int\" Dimensions=\"1\" Format=\"XML\" Precision=\"4\">56</DataItem>\r\n",
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" </Attribute>\r\n",
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" <Attribute Center=\"Node\" Name=\"Density\" Type=\"Vector\">\r\n",
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" <DataItem DataType=\"Float\" Dimensions=\"4\" Format=\"XML\" Precision=\"4\">1.3 2.4000001 4.5 6.6999998</DataItem>\r\n",
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" </Attribute>\r\n",
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" </Grid>\r\n",
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" </Grid>\r\n",
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" </Domain>\r\n",
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"</Xdmf>\r\n"
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]
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}
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],
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"source": [
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"!cat testdata.xmf"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This time Xdmf decided to write results directly to the xml file. If the model is bigger the correct format is"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" <?xml version=\"1.0\" encoding=\"utf-8\"?>\n",
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" <Xdmf xmlns:xi=\"http://www.w3.org/2001/XInclude\" Version=\"2.1\">\n",
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" <Domain>\n",
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" <Grid CollectionType=\"Temporal\" GridType=\"Collection\" Name=\"Collection\">\n",
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" <Geometry Type=\"None\"/>\n",
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" <Topology Dimensions=\"0\" Type=\"NoTopology\"/>\n",
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" <Grid Name=\"Grid\">\n",
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" <Time Value=\"0\"/>\n",
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" <Geometry Type=\"XYZ\">\n",
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" <DataItem DataType=\"Float\" Dimensions=\"1260999\" Format=\"HDF\" Precision=\"4\">model.h5:Data16</DataItem>\n",
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" </Geometry>\n",
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" <Topology Dimensions=\"292001\" Type=\"Mixed\">\n",
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" <DataItem DataType=\"Int\" Dimensions=\"3046831\" Format=\"HDF\" Precision=\"4\">model.h5:Data17</DataItem>\n",
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" </Topology>\n",
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" <Attribute Center=\"Cell\" Name=\"Temperature field\" Type=\"Scalar\">\n",
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" <DataItem DataType=\"Int\" Dimensions=\"292001\" Format=\"HDF\" Precision=\"4\">model.h5:Data18</DataItem>\n",
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" </Attribute>\n",
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" <Attribute Center=\"Node\" Name=\"Density\" Type=\"Vector\">\n",
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" <DataItem DataType=\"Float\" Dimensions=\"292001\" Format=\"HDF\" Precision=\"4\">model.h5:Data19</DataItem>\n",
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" </Attribute>\n",
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" </Grid>\n",
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" </Grid>\n",
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" </Domain>\n",
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" </Xdmf>\n",
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"\n",
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"\n",
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"Structure of h5 file\n",
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"\n",
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"\n",
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" File(filename=model.h5, title='', mode='r+', root_uep='/', filters=Filters(complevel=0, shuffle=False, fletcher32=False, least_significant_digit=None)) \n",
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" / (RootGroup) '' \n",
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" /Data0 (EArray(1125135,)) ''\n",
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" atom := Float32Atom(shape=(), dflt=0.0)\n",
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" maindim := 0 \n",
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" flavor := 'numpy' \n",
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" byteorder := 'little' \n",
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" chunkshape := (1000,) \n",
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" /Data1 (EArray(2680009,)) ''\n",
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" atom := Int32Atom(shape=(), dflt=0)\n",
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" maindim := 0 \n",
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" flavor := 'numpy' \n",
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" byteorder := 'little' \n",
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" chunkshape := (1000,) \n",
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" ...\n",
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"\n",
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"\n",
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" In [7]: d.root.Data0[:]\n",
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" Out[7]:\n",
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" array([ 302.10440063, 222.19999695, 20.38028908, ..., -230. ,\n",
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" 0. , 7.33333015], dtype=float32)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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