notebook to show how to use python to call matlab mtex to convert pol…

…e figure to texture.

with this, users don't  have to run mtex gui.

notebooks/testmatlab-mtex-2.ipynb

@@ -0,0 +1,312 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/SNS/users/lj7/imaging/testmtex\n"
+     ]
+    }
+   ],
+   "source": [
+    "workdir = \"/SNS/users/lj7/imaging/testmtex\"\n",
+    "!mkdir -p {workdir}\n",
+    "%cd {workdir}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os, numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Modules"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Overwriting startup.m\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%file startup.m\n",
+    "addpath('/HFIR/CG1D/shared/mtex/mtex-4.5.2/')\n",
+    "startup_mtex"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Overwriting odf2VPSC.m\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%file odf2VPSC.m\n",
+    "function odf2VPSC(odf,filename,varargin)\n",
+    "% export an ODF to the VPSC format\n",
+    "%\n",
+    "%% Syntax\n",
+    "% export_VPSC(odf,'file.txt','points',points)\n",
+    "%\n",
+    "%% Input\n",
+    "%  odf      - ODF to be exported\n",
+    "%  filename - name of the ascii file\n",
+    "%\n",
+    "%% Options\n",
+    "%  points    - number of orientations\n",
+    "%\n",
+    "%% See also\n",
+    "% ODFImportExport\n",
+    "  \n",
+    "% get number of points\n",
+    "points = get_option(varargin,'points',5000);\n",
+    "\n",
+    "% simulate orientations\n",
+    "orientations = calcOrientations(odf,points,varargin{:});\n",
+    "\n",
+    "% export\n",
+    "export_VPSC(orientations,filename,varargin{:});\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Writing polfig2VPSC2.m\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%file polfig2VPSC.m\n",
+    "function polfig2VPSC(polfigpath, hkls, outpath)\n",
+    "%% Import Script for PoleFigure Data\n",
+    "\n",
+    "%% Specify Crystal and Specimen Symmetries\n",
+    "% crystal symmetry\n",
+    "CS = crystalSymmetry('1', [1 1 1], [90,90,90]*degree, 'X||a', 'Y||b*', 'Z||c*', 'color', 'light blue');\n",
+    "\n",
+    "% specimen symmetry\n",
+    "SS = specimenSymmetry('1');\n",
+    "\n",
+    "% plotting convention\n",
+    "setMTEXpref('xAxisDirection','north');\n",
+    "setMTEXpref('zAxisDirection','outOfPlane');\n",
+    "\n",
+    "%% Specify File Names\n",
+    "\n",
+    "% path to files\n",
+    "fname = [polfigpath];\n",
+    "\n",
+    "%% Specify Miller Indice\n",
+    "nhkl = size(hkls, 1);\n",
+    "h = arrayfun( @(IDX) Miller(mat2cell(hkls(IDX,:), 1, ones(1, 3)), CS), (1:nhkl).', 'uniform', 0);\n",
+    "\n",
+    "%% Import the Data\n",
+    "\n",
+    "% create a Pole Figure variable containing the data\n",
+    "pf = loadPoleFigure(fname,h,CS,SS,'interface','siemens');\n",
+    "\n",
+    "odf = calcODF(pf);\n",
+    "odf2VPSC(odf, outpath);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Start matlab"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matlab.engine, matlab\n",
+    "_ml_engine = matlab.engine.start_matlab()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hkls = matlab.double([[1,1,1], [2,0,0], [2,2,0], [2,2,2] ])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import StringIO\n",
+    "out = StringIO.StringIO()\n",
+    "err = StringIO.StringIO()\n",
+    "\n",
+    "_ml_engine.polfig2VPSC(\n",
+    "    \"/SNS/users/lj7/dv/imaging/braggedgemodeling/tests/data/VULCAN.rpf\", \n",
+    "    hkls,\n",
+    "    \"tmp.txt\",\n",
+    "    nargout=0, stdout=out, stderr=err\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "------ MTEX -- PDF to ODF inversion ------------------\n",
+      "Call c-routine\n",
+      "initialize solver\n",
+      "start iteration\n",
+      "error: 8.9615E-02 2.9824E-02 2.3061E-02 2.0660E-02 1.9165E-02 1.8185E-02 1.7371E-02 1.6778E-02 1.6254E-02 1.5831E-02 1.5434E-02 \n",
+      "Finished PDF-ODF inversion.\n",
+      "error: 1.5434E-02\n",
+      "alpha: 1.0301E+00 9.2333E-01 1.0223E+00 1.0214E+00 \n",
+      "required time: 5s\n",
+      "ghost correction\n",
+      "calculate with fixed background 0.49\n",
+      "initialize solver\n",
+      "start iteration\n",
+      "error: 2.7973E-01 1.0409E-01 8.0557E-02 7.3001E-02 6.7023E-02 6.3385E-02 6.0057E-02 5.7743E-02 5.5601E-02 5.4001E-02 5.2487E-02 \n",
+      "Finished PDF-ODF inversion.\n",
+      "error: 5.2487E-02\n",
+      "alpha: 1.0334E+00 9.2192E-01 1.0099E+00 1.0255E+00 \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print out.getvalue()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print err.getvalue()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Exit matlab"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "_ml_engine.exit()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "python2-default at jnrk-sns-analysis",
+   "language": "python",
+   "name": "jnrk-sns-analysis-python2-default"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.12"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": true
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}