From 068de907579bf2cc907e702e2d546152a0acbcdd Mon Sep 17 00:00:00 2001
From: Cristian Lalescu <Cristian.Lalescu@ds.mpg.de>
Date: Tue, 30 Jun 2015 13:57:52 +0200
Subject: [PATCH] remove ipython notebooks

---
 test.ipynb           | 153 ------------------------
 test_shuffling.ipynb | 270 -------------------------------------------
 2 files changed, 423 deletions(-)
 delete mode 100644 test.ipynb
 delete mode 100644 test_shuffling.ipynb

diff --git a/test.ipynb b/test.ipynb
deleted file mode 100644
index 14485652..00000000
--- a/test.ipynb
+++ /dev/null
@@ -1,153 +0,0 @@
-{
- "metadata": {
-  "name": "",
-  "signature": "sha256:70c4b065d524fe79b51e885d5e77aec8982c6ae0996146ba76aa979790c214b7"
- },
- "nbformat": 3,
- "nbformat_minor": 0,
- "worksheets": [
-  {
-   "cells": [
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "import numpy as np\n",
-      "import subprocess\n",
-      "import pyfftw"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [],
-     "prompt_number": 1
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "def generate_data_3D(\n",
-      "        n,\n",
-      "        dtype = np.complex128,\n",
-      "        p = 1.5):\n",
-      "    \"\"\"\n",
-      "    generate something that has the proper shape\n",
-      "    \"\"\"\n",
-      "    assert(n % 2 == 0)\n",
-      "    a = np.zeros((n, n, n/2+1), dtype = dtype)\n",
-      "    a[:] = np.random.randn(*a.shape) + 1j*np.random.randn(*a.shape)\n",
-      "    k, j, i = np.mgrid[-n/2+1:n/2+1, -n/2+1:n/2+1, 0:n/2+1]\n",
-      "    k = (k**2 + j**2 + i**2)**.5\n",
-      "    k = np.roll(k, n//2+1, axis = 0)\n",
-      "    k = np.roll(k, n//2+1, axis = 1)\n",
-      "    a /= k**p\n",
-      "    a[0, :, :] = 0\n",
-      "    a[:, 0, :] = 0\n",
-      "    a[:, :, 0] = 0\n",
-      "    ii = np.where(k == 0)\n",
-      "    a[ii] = 0\n",
-      "    ii = np.where(k > n/3)\n",
-      "    a[ii] = 0\n",
-      "    return a\n",
-      "\n",
-      "n = 32\n",
-      "\n",
-      "Kdata0 = generate_data_3D(n, p = 2).astype(np.complex64)\n",
-      "Kdata0.tofile(\"Kdata0\")"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
-      {
-       "output_type": "stream",
-       "stream": "stderr",
-       "text": [
-        "-c:15: RuntimeWarning: divide by zero encountered in divide\n"
-       ]
-      }
-     ],
-     "prompt_number": 2
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "def compute_cpp_data(\n",
-      "        branch = None):\n",
-      "    if not (type(branch) == type(None)):\n",
-      "        subprocess.call(['git', 'checkout', branch])\n",
-      "    if subprocess.call(['make', 'main_fluid_solver.elf']) == 0:\n",
-      "        subprocess.call(['time',\n",
-      "                         'mpirun',\n",
-      "                         '-np',\n",
-      "                         '4',\n",
-      "                         './main_fluid_solver.elf'])\n",
-      "        return np.fromfile('Kdata1')\n",
-      "    else:\n",
-      "        print ('compilation error')\n",
-      "        return None\n",
-      "\n",
-      "Kdata1 = compute_cpp_data()"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [],
-     "prompt_number": 4
-    },
-    {
-     "cell_type": "code",
-     "collapsed": true,
-     "input": [
-      "distance = np.max(np.abs(Rdata_py - Rdata), axis = (1, 2, 3, 4))\n",
-      "print(np.max(distance))\n",
-      "if np.max(distance) > 1e-5:\n",
-      "    ax = plt.figure(figsize=(6,2)).add_subplot(111)\n",
-      "    ax.plot(distance)\n",
-      "    i0 = np.random.randint(8)\n",
-      "    i1 = np.random.randint(8)\n",
-      "    i2 = np.random.randint(8)\n",
-      "    z = cm.grid3D_to_zindex(np.array([i0, i1, i2]))\n",
-      "    #z = 0\n",
-      "    print(cm.zindex_to_grid3D(z))\n",
-      "    s = np.max(np.abs(Rdata_py[None, z, :, :, :, 1] - Rdata[..., 1]),\n",
-      "               axis = (1, 2, 3))\n",
-      "    z1 = np.argmin(s)\n",
-      "    print(z, z1, s[z1])\n",
-      "        #print(Rdata[z1] - Rdata_py[z1])\n",
-      "    ta0 = Rdata_py.ravel()\n",
-      "    ta1 = Rdata.ravel()\n",
-      "    print (Rdata_py[254:259, 7, 4, 3, 1])\n",
-      "    print (Rdata[254:259, 7, 4, 3, 1])\n",
-      "    print (ta0[ta0.shape[0]/2-1:ta0.shape[0]/2+7])\n",
-      "    print (ta1[ta1.shape[0]/2-1:ta1.shape[0]/2+7])\n",
-      "else:\n",
-      "    print('distance is small')\n",
-      "print(np.max(np.abs(Rdata)))"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
-      {
-       "output_type": "stream",
-       "stream": "stdout",
-       "text": [
-        "1.90735e-06\n",
-        "distance is small\n",
-        "15.316\n"
-       ]
-      }
-     ],
-     "prompt_number": 7
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [],
-     "language": "python",
-     "metadata": {},
-     "outputs": []
-    }
-   ],
-   "metadata": {}
-  }
- ]
-}
\ No newline at end of file
diff --git a/test_shuffling.ipynb b/test_shuffling.ipynb
deleted file mode 100644
index 2284a7dd..00000000
--- a/test_shuffling.ipynb
+++ /dev/null
@@ -1,270 +0,0 @@
-{
- "metadata": {
-  "name": "",
-  "signature": "sha256:46290caaf0d19fceaf2c8987f305c20f9083f9d3d3d0ee8ef3987689c3fccbf0"
- },
- "nbformat": 3,
- "nbformat_minor": 0,
- "worksheets": [
-  {
-   "cells": [
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "import numpy as np\n",
-      "import subprocess\n",
-      "%matplotlib inline\n",
-      "import matplotlib.pyplot as plt\n",
-      "import pyfftw"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [],
-     "prompt_number": 1
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "def generate_data_3D(\n",
-      "        n,\n",
-      "        dtype = np.complex128,\n",
-      "        p = 1.5):\n",
-      "    \"\"\"\n",
-      "    generate something that has the proper shape\n",
-      "    \"\"\"\n",
-      "    assert(n % 2 == 0)\n",
-      "    a = np.zeros((n, n, n/2+1), dtype = dtype)\n",
-      "    a[:] = np.random.randn(*a.shape) + 1j*np.random.randn(*a.shape)\n",
-      "    k, j, i = np.mgrid[-n/2+1:n/2+1, -n/2+1:n/2+1, 0:n/2+1]\n",
-      "    k = (k**2 + j**2 + i**2)**.5\n",
-      "    k = np.roll(k, n//2+1, axis = 0)\n",
-      "    k = np.roll(k, n//2+1, axis = 1)\n",
-      "    a /= k**p\n",
-      "    a[0, :, :] = 0\n",
-      "    a[:, 0, :] = 0\n",
-      "    a[:, :, 0] = 0\n",
-      "    ii = np.where(k == 0)\n",
-      "    a[ii] = 0\n",
-      "    ii = np.where(k > n/3)\n",
-      "    a[ii] = 0\n",
-      "    return a\n",
-      "\n",
-      "n = 31*4\n",
-      "N = 256\n",
-      "\n",
-      "Kdata0 = generate_data_3D(n, p = 2).astype(np.complex64)\n",
-      "Kdata1 = generate_data_3D(n, p = 2).astype(np.complex64)\n",
-      "Kdata2 = generate_data_3D(n, p = 2).astype(np.complex64)\n",
-      "Kdata0.T.copy().astype('>c8').tofile(\"Kdata0\")\n",
-      "Kdata1.T.copy().astype('>c8').tofile(\"Kdata1\")\n",
-      "Kdata2.T.copy().astype('>c8').tofile(\"Kdata2\")"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
-      {
-       "output_type": "stream",
-       "stream": "stderr",
-       "text": [
-        "-c:15: RuntimeWarning: divide by zero encountered in divide\n"
-       ]
-      }
-     ],
-     "prompt_number": 2
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "def padd_with_zeros(\n",
-      "        a,\n",
-      "        n,\n",
-      "        odtype = None):\n",
-      "    if (type(odtype) == type(None)):\n",
-      "        odtype = a.dtype\n",
-      "    assert(a.shape[0] <= n)\n",
-      "    b = np.zeros((n, n, n/2 + 1), dtype = odtype)\n",
-      "    m = a.shape[0]\n",
-      "    b[     :m/2,      :m/2, :m/2+1] = a[     :m/2,      :m/2, :m/2+1]\n",
-      "    b[     :m/2, n-m/2:   , :m/2+1] = a[     :m/2, m-m/2:   , :m/2+1]\n",
-      "    b[n-m/2:   ,      :m/2, :m/2+1] = a[m-m/2:   ,      :m/2, :m/2+1]\n",
-      "    b[n-m/2:   , n-m/2:   , :m/2+1] = a[m-m/2:   , m-m/2:   , :m/2+1]\n",
-      "    return b\n",
-      "\n",
-      "def transform_py(bla):\n",
-      "    b = padd_with_zeros(bla, N)\n",
-      "    c = np.zeros((N, N, N), np.float32)\n",
-      "    t = pyfftw.FFTW(\n",
-      "        b, c,\n",
-      "        axes = (0, 1, 2),\n",
-      "        direction = 'FFTW_BACKWARD',\n",
-      "        flags = ('FFTW_ESTIMATE',),\n",
-      "        threads = 2)\n",
-      "    t.execute()\n",
-      "    return c\n",
-      "\n",
-      "import chichi_misc as cm\n",
-      "\n",
-      "def array_to_8cubes(\n",
-      "    a,\n",
-      "    odtype = None):\n",
-      "    assert(len(a.shape) >= 3)\n",
-      "    assert((a.shape[0] % 8 == 0) and\n",
-      "           (a.shape[1] % 8 == 0) and\n",
-      "           (a.shape[2] % 8 == 0))\n",
-      "    if type(odtype) == type(None):\n",
-      "        odtype = a.dtype\n",
-      "    c = np.zeros(\n",
-      "        ((((a.shape[0] // 8)*(a.shape[1] // 8)*(a.shape[2] // 8)),) +\n",
-      "         (8, 8, 8) +\n",
-      "         a.shape[3:]),\n",
-      "        dtype = odtype)\n",
-      "    zi = np.zeros( c.shape[0], dtype = np.int)\n",
-      "    ri = np.zeros((c.shape[0], 3, 2), dtype = np.int)\n",
-      "    ii = 0\n",
-      "    for k in range(a.shape[0]//8):\n",
-      "        for j in range(a.shape[1]//8):\n",
-      "            for i in range(a.shape[2]//8):\n",
-      "                tindex = np.array([k, j, i])\n",
-      "                zi[ii] = cm.grid3D_to_zindex(tindex)\n",
-      "                ri[ii, 0] = np.array([8*tindex[0], 8*(tindex[0]+1)])\n",
-      "                ri[ii, 1] = np.array([8*tindex[1], 8*(tindex[1]+1)])\n",
-      "                ri[ii, 2] = np.array([8*tindex[2], 8*(tindex[2]+1)])\n",
-      "                ii += 1\n",
-      "    for ii in range(zi.shape[0]):\n",
-      "        c[zi[ii]] = a[ri[ii, 0, 0]:ri[ii, 0, 1],\n",
-      "                      ri[ii, 1, 0]:ri[ii, 1, 1],\n",
-      "                      ri[ii, 2, 0]:ri[ii, 2, 1]]\n",
-      "    return c\n",
-      "\n",
-      "d0 = transform_py(Kdata0)\n",
-      "d1 = transform_py(Kdata1)\n",
-      "d2 = transform_py(Kdata2)\n",
-      "\n",
-      "Rdata_py_tmp = np.array([d0, d1, d2]).transpose((1, 2, 3, 0))\n",
-      "\n",
-      "Rdata_py = array_to_8cubes(Rdata_py_tmp)\n",
-      "\n",
-      "# i0 = np.random.randint(16)\n",
-      "# i1 = np.random.randint(16)\n",
-      "# i2 = np.random.randint(16)\n",
-      "# z = cm.grid3D_to_zindex(np.array([i0, i1, i2]))"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [],
-     "prompt_number": 3
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "def compute_cpp_data(\n",
-      "        branch = None,\n",
-      "        nfiles = 16):\n",
-      "    if not (type(branch) == type(None)):\n",
-      "        subprocess.call(['git', 'checkout', branch])\n",
-      "    if subprocess.call(['make', 'full.elf']) == 0:\n",
-      "        subprocess.call([#'valgrind',\n",
-      "                         #'--tool=callgrind',\n",
-      "                         #'--callgrind-out-file=tmp.txt',\n",
-      "                         'time',\n",
-      "                         'mpirun',\n",
-      "                         '-np',\n",
-      "                         '4',\n",
-      "                         './full.elf',\n",
-      "                         '{0}'.format(n),\n",
-      "                         '{0}'.format(N),\n",
-      "                         '{0}'.format(nfiles),\n",
-      "                         '3'])\n",
-      "    else:\n",
-      "        print ('compilation error')\n",
-      "        return None\n",
-      "    \n",
-      "def get_cpp_data(\n",
-      "        branch = None,\n",
-      "        run = True,\n",
-      "        nfiles = 16):\n",
-      "    if run:\n",
-      "        for nf in range(nfiles):\n",
-      "            subprocess.call(\n",
-      "                ['rm',\n",
-      "                 'Rdata_z{0:0>7x}'.format(nf*Rdata_py.shape[0]//nfiles)])\n",
-      "        compute_cpp_data(branch, nfiles = nfiles)\n",
-      "    Rdata = []\n",
-      "    for nf in range(nfiles):\n",
-      "        Rdata.append(np.fromfile(\n",
-      "        'Rdata_z{0:0>7x}'.format(nf*Rdata_py.shape[0]//nfiles),\n",
-      "        dtype = np.float32).reshape(-1, 8, 8, 8, 3))\n",
-      "    return np.concatenate(Rdata)\n",
-      "\n",
-      "#Rdata = get_cpp_data(branch = 'develop')\n",
-      "# develop says 30 secs, inplace fft is 28 secs\n",
-      "#Rdata = get_cpp_data(branch = 'feature-inplace_fft')\n",
-      "Rdata = get_cpp_data(run = True, nfiles = 16)"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [],
-     "prompt_number": 6
-    },
-    {
-     "cell_type": "code",
-     "collapsed": true,
-     "input": [
-      "distance = np.max(np.abs(Rdata_py - Rdata), axis = (1, 2, 3, 4))\n",
-      "print(np.max(distance))\n",
-      "if np.max(distance) > 1e-5:\n",
-      "    ax = plt.figure(figsize=(6,2)).add_subplot(111)\n",
-      "    ax.plot(distance)\n",
-      "    i0 = np.random.randint(8)\n",
-      "    i1 = np.random.randint(8)\n",
-      "    i2 = np.random.randint(8)\n",
-      "    z = cm.grid3D_to_zindex(np.array([i0, i1, i2]))\n",
-      "    #z = 0\n",
-      "    print(cm.zindex_to_grid3D(z))\n",
-      "    s = np.max(np.abs(Rdata_py[None, z, :, :, :, 1] - Rdata[..., 1]),\n",
-      "               axis = (1, 2, 3))\n",
-      "    z1 = np.argmin(s)\n",
-      "    print(z, z1, s[z1])\n",
-      "        #print(Rdata[z1] - Rdata_py[z1])\n",
-      "    ta0 = Rdata_py.ravel()\n",
-      "    ta1 = Rdata.ravel()\n",
-      "    print (Rdata_py[254:259, 7, 4, 3, 1])\n",
-      "    print (Rdata[254:259, 7, 4, 3, 1])\n",
-      "    print (ta0[ta0.shape[0]/2-1:ta0.shape[0]/2+7])\n",
-      "    print (ta1[ta1.shape[0]/2-1:ta1.shape[0]/2+7])\n",
-      "else:\n",
-      "    print('distance is small')\n",
-      "print(np.max(np.abs(Rdata)))"
-     ],
-     "language": "python",
-     "metadata": {},
-     "outputs": [
-      {
-       "output_type": "stream",
-       "stream": "stdout",
-       "text": [
-        "1.90735e-06\n",
-        "distance is small\n",
-        "15.316\n"
-       ]
-      }
-     ],
-     "prompt_number": 7
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [],
-     "language": "python",
-     "metadata": {},
-     "outputs": []
-    }
-   ],
-   "metadata": {}
-  }
- ]
-}
\ No newline at end of file
-- 
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