working

Untitled.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import numpy\n",
+    "import multiprocessing\n",
+    "import time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "pool = multiprocessing.dummy.Pool()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Control: No powers\n",
+      "59985997.0712 0.139564037323\n",
+      "Single process\n",
+      "15981208.9044 3.03516697884\n",
+      "Several processes\n",
+      "15981208.9044 1.16520905495\n"
+     ]
+    }
+   ],
+   "source": [
+    "def test(n):\n",
+    "    x = numpy.random.rand(n)\n",
+    "    \n",
+    "    print 'Control: No powers'\n",
+    "    acc = numpy.zeros(n)\n",
+    "    now = time.time()\n",
+    "    for i in range(30):\n",
+    "        acc += x\n",
+    "    s = acc.sum()\n",
+    "    print s, time.time() - now\n",
+    "    \n",
+    "    print 'Single process'\n",
+    "    acc = numpy.zeros(n)\n",
+    "    now = time.time()\n",
+    "    for i in range(30):\n",
+    "        acc += x ** i\n",
+    "    s = acc.sum()\n",
+    "    print s, time.time() - now\n",
+    "    \n",
+    "    print 'Several processes'\n",
+    "    acc = numpy.zeros(n)\n",
+    "    now = time.time()\n",
+    "    def pow(i):\n",
+    "        return x ** i\n",
+    "    exps = pool.map(pow, range(30))\n",
+    "    for exp in exps:\n",
+    "        acc += exp\n",
+    "    s = acc.sum()\n",
+    "    print s, time.time() - now\n",
+    "\n",
+    "test(4000000)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def test(x):\n",
+    "    return x * x\n",
+    "\n",
+    "p = Process(target=test, args=(3,))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "p.start()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "p."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}

Untitled1.ipynb

@@ -0,0 +1,44 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import stitching\n",
+    "import spimage\n",
+    "import cPickle as pickle\n",
+    "\n",
+    "job = pickle.load(open('conc_1.job', 'wb'))\n",
+    "\n",
+    "job.detail_transfer_stitch_pt_2(canvas_scale=2, detail_transfer_radius=33, edge_blend_radius=5)\n",
+    "\n",
+    "job.detail_transfer_stitch_output().save('conc.png')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}