From 1c2653a3cfcff4662686fa37fb45a1b786c22e33 Mon Sep 17 00:00:00 2001
From: Markus Holzer <markus.holzer@fau.de>
Date: Mon, 11 Jan 2021 20:14:48 +0100
Subject: [PATCH] Extended Test suit
---
.../01_tutorial_getting_started.ipynb | 490 +++++++++---------
.../04_tutorial_advection_diffusion.ipynb | 16 +-
pystencils/backends/dot.py | 4 +-
pystencils/cpu/kernelcreation.py | 4 -
.../datahandling/parallel_datahandling.py | 2 +-
pystencils/fd/spatial.py | 33 --
pystencils/field.py | 12 +-
.../kerncraft_coupling/kerncraft_interface.py | 6 -
pystencils/stencil.py | 6 +-
pystencils/transformations.py | 9 +
pystencils_tests/test_address_of.py | 6 +-
pystencils_tests/test_aligned_array.py | 4 +-
pystencils_tests/test_basic_usage_llvm.ipynb | 231 +++++----
pystencils_tests/test_blocking.py | 13 +
pystencils_tests/test_boundary.py | 131 +++++
pystencils_tests/test_cudagpu.py | 6 +
.../datahandling_parallel_load_test/dst.dat | Bin 0 -> 304 bytes
.../datahandling_parallel_load_test/src.dat | Bin 0 -> 304 bytes
.../datahandling_parallel_save_test/dst.dat | Bin 0 -> 304 bytes
.../datahandling_parallel_save_test/src.dat | Bin 0 -> 304 bytes
pystencils_tests/test_datahandling.py | 10 +-
.../test_datahandling_parallel.py | 73 +++
pystencils_tests/test_dot_printer.ipynb | 314 +++++++++++
pystencils_tests/test_field.py | 30 ++
pystencils_tests/test_finite_differences.py | 18 +-
.../test_jupyter_extensions.ipynb | 32 +-
pystencils_tests/test_kerncraft_coupling.py | 15 +-
pystencils_tests/test_llvm.py | 126 +++++
pystencils_tests/test_loop_cutting.py | 6 +
pystencils_tests/test_stencil_plot.ipynb | 62 +++
pystencils_tests/test_sympy_optimizations.py | 38 +-
pystencils_tests/test_sympyextensions.py | 38 ++
pystencils_tests/test_transformations.py | 25 +
pystencils_tests/test_types.py | 107 +++-
pystencils_tests/test_vectorization.py | 37 ++
.../test_vectorization_specific.py | 5 -
pytest.ini | 2 +-
37 files changed, 1447 insertions(+), 464 deletions(-)
create mode 100644 pystencils_tests/test_data/datahandling_parallel_load_test/dst.dat
create mode 100644 pystencils_tests/test_data/datahandling_parallel_load_test/src.dat
create mode 100644 pystencils_tests/test_data/datahandling_parallel_save_test/dst.dat
create mode 100644 pystencils_tests/test_data/datahandling_parallel_save_test/src.dat
create mode 100644 pystencils_tests/test_dot_printer.ipynb
create mode 100644 pystencils_tests/test_stencil_plot.ipynb
create mode 100644 pystencils_tests/test_transformations.py
diff --git a/doc/notebooks/01_tutorial_getting_started.ipynb b/doc/notebooks/01_tutorial_getting_started.ipynb
index 70b3c2a8a..89a593710 100644
--- a/doc/notebooks/01_tutorial_getting_started.ipynb
+++ b/doc/notebooks/01_tutorial_getting_started.ipynb
@@ -66,7 +66,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "3.93 ms ± 40 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+ "7.11 ms ± 137 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
]
}
],
@@ -89,12 +89,12 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
- "$\\displaystyle {{dst}_{(0,0)}} \\leftarrow \\frac{{{src}_{(-1,0)}}}{4} + \\frac{{{src}_{(0,-1)}}}{4} + \\frac{{{src}_{(0,1)}}}{4} + \\frac{{{src}_{(1,0)}}}{4}$"
+ "$\\displaystyle {{dst}_{(0,0)}} \\leftarrow \\frac{{{src}_{(1,0)}}}{4} + \\frac{{{src}_{(0,1)}}}{4} + \\frac{{{src}_{(0,-1)}}}{4} + \\frac{{{src}_{(-1,0)}}}{4}$"
],
"text/plain": [
- " src_W src_S src_N src_E\n",
+ " src_E src_N src_S src_W\n",
"dst_C := ───── + ───── + ───── + ─────\n",
" 4 4 4 4 "
]
@@ -119,7 +119,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAMQAAADTCAYAAADedbxIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAJ/UlEQVR4nO3cf2jU9x3H8dcnl8SL8aLV09hpbeta/ymMunWyVufagZWIPwgbxT8srLKNVtuZjZU66B+CcxUGXaDgNoaw1spa21VQ8AyDCjZaGLhNGJu/t4Qq/jhqYrTxx10+++OS2zuXXO5yuXy/t93zAYHc3febe6PfZ+5733zv67z3ApBRE/YAQCUhCMCoDXuAauMSyaik5ZIWSoqMsehtSScknfQtcfZrA+J4DxEcl0jOk/SupC+NY7UOST/2LfH05EwFi12mYL2s8cUgSSslfWsSZsEoCCJY3yhxvSfLOgXyIohgNZa43tSyToG8CCJYbsQ9fddrtPnpBWpd8KjOnawvej1MCoIIW7RxQNvfv6glz/aFPQoIInx19dLMZo4gVQiCAAyCAAyCAAxO3agEW1vnqetUVJcu1Gvlhh6t3ngj7JGqFUFUgp37L4Y9AjLYZQIMggAMdpnCtmr2oryPHbp2JsBJIIII39BG37E3pt3b5mjf2fMhT1TV2GWqBANp6djBmGbNTYU9SrUjiErQsbdJS9f0yXEOX9gIImzplNR5IKYV6zm5rwIQRNgO72nSsrV9qhnr49UICkGErft0vT7eN1Ovrl6kK911am+bE/ZI1YyjTGF78Y2kLv+7Sem0tOMFr7b2q2GPVM14hQjbnf4GDQxk9pdef9uJq6CEiiDCdrPnPnk/eHjJS/03p4U7UHUjiGAN//WfTtfoTv9/LzzgfY1u9txXcD1MGoII1q3ht3qnj1ji3t2oUndz39vdGrEcJgVBBOt49jvvpVu9Zncpe7/Tzd4ZOesdC2A2iCCC9pak7uytmtqUIpGUnMvsEkUimdvDHZTUGdiEVY5ruwbMJZJ1ylyJb6GGDnt/cmCx/nJkk7b86gdm0duSTviW+D+Dn7J6EUQFcM61SvrI5+4+IXDsMgEGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQAGQQBG7VgPukQyIsnledj7lni6/CMBE1fqtuu897k/aL6krZKWSWoo8LxJSQlJv/Qt8TvjmhhZzrlWSR957/P9B6IILpH8sqRXJT0laUqBxa9IOijpTRvHsFeIwareljS/yBnikp6X1CjpZ0WuA5SdSySjkt5RZpssRrOk70uql7Rj6M7c9xBPqPgYrFWDAwFhWabiY7DWuUQy20FuEA+UOExU0uwS1wXKYUGJ602XFBu6kRtEZMTifddrtPnpBWpd8KjOnawf4wdzxAphGrn9Fb/tZt86FN6Io40D2v7+RS15tq+kMYGwlLDtFg6irl6a2czhVfzvKWHbZTcHMAgCMAgCMMY8dSNra+s8dZ2K6tKFeq3c0KPVG29M8lxAeYxz2y0uiJ37L45nBudcg6TvSvqppE7v/ebxrA+MxjlXJ+nvg1/tymxbfsyVxrntlnWXyTn3mHPuN5KuSdol6SuSFpfzOVDVIpIekdQq6ZCkLufcT5xzM8v1BMW9QhRys7dJbSsSkh6SVJfzc+udc81leZ7/X9MliX+ngqKSvDK/yKcNfm2XtEPvvPEPPbelQdGp/RN5gsJBrJq9KO9jh66dkST1XJur1L25eZb6mqTLJcxWjfh3Gr+pkqTrVxcreclp/iNnso8Us+3mKBzE0Iode2PavW2O9p09P2KZWXM/05SGc5KeVKZge6Lfp977pwo+TxXj9O/iOOeikm5q+ClGmb9C3//Qn9X8wMJhKxSz7eYo7j3EQFo6djCmWXNToz7eMO0L/fb495TZZdoh6Wp2UKC8nKR7kvolnZD0Q0mz9dyW91Q35d6IpQttuzmKC6Jjb5OWrumTG/sXmPf+svf+55Lul/QdZT489HFRzwEUlpJ0XNKvJT3uvX/Ce/+e9z7/h9OK3HaHFA4inZI6D8S0Yn3Rv/G99wPe+z9571d5718vdj1gLN77lPf+m977Ld77Ud8DDFPCtls4iMN7mrRsbZ9qRp4ZDlS0ErbdwkF0n67XkQ+a9Nq6+brSXaf2tjkTmREITAnbbuGjTC/tTGa/37T8QbW1X53YlEBASth2x/eX6l1Hu8Y/FVABitx2OdsVMAgCMHKDKOqPF3lMZF1goibyMefsH/Ryg/hXiT/wljJnuAJhuVDiekmZsypyg/irpNMl/NA/+pb43RIHAsrhuKTuEtbb51vi2c9UDDvs6lvi3iWSL0h6RZkroTUp/wVjB5Q5OzMh6XclDAKUjW+J33OJ5POSXpa0VJnLq+bbdtOSLilzbdff2wdGXOwYweNs18rBUSbAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAIAjAqA17gGrjEskmSSskLZQUkSTt+PAx/e2oXCK51SzaL+mEpE99Szwd+KBVynnvw56harhE8mFJ70qKy3vpctfDGkjXynuXWcBl/jMapvVqZvPVwdU6Jb3oW+L3wpi52rDLFKzNkuKSJJdpIBuD/T4Ssa8IyyQ9E8x4IIhgfX3YrWkzPs++KliN03ty7lkyiTPBIIhgTR12qzF2Y8QSdVP6VVuX+56hYRJngkEQYaqJeKXTffrFRumVb0uXLgwoNuPzUZZ0o9yHSUAQYZvVfF0/etPrq89Icl7Rxi/CHqmaEUTYGqff0fR4SpIUndqXfbONUBBEJZg2uJs0paEv5EmqHn+YqwSxGb2qrWvIOdyKEPAKARi8QlSCra3z1HUqqksX6rVyQ49Wbxx5OBaBIIhKsHP/xbBHQAa7TIBBEIDBLlPYVs1elPexQ9fOBDgJRBDhG9roO/bGtHvbHO07ez7kiaoau0yVYCAtHTsY06y5qbBHqXYEUQk69jZp6RpO26gABBG2dErqPBDTivWctlEBCCJsh/c0adnaPtVEwp4EIojwdZ+u15EPmvTauvm60l2n9rY5YY9UzTjKFLaXdiaz329a/qDa2q+OsTQmGa8QlWTX0a6wR6h2BAEYBBGsUi+CxcWzAkIQwSr10CqngweEIIL1SYnrdZZ1CuRFEMF6S9Lpca7zB0nHJ2EWjIJruwbMJZJO0uPKXOx4rMPetyWd8C3xzwIZDJIIAhiGXSbAIAjA+A9JIWcDKWIk7QAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 216x216 with 1 Axes>"
]
@@ -180,7 +180,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "643 µs ± 8.66 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
+ "1.49 ms ± 5.93 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
]
}
],
@@ -261,7 +261,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle x^{2} \\left(x + y + 5\\right) + x^{2}$"
],
@@ -294,7 +294,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle x^{3} + x^{2} y + 6 x^{2}$"
],
@@ -319,7 +319,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle x^{2} \\left(x + y + 6\\right)$"
],
@@ -344,7 +344,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle x^{2} \\left(x + \\cos{\\left(x \\right)} + 5\\right) + x^{2}$"
],
@@ -376,7 +376,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle x^{2} \\left(x + y + 5\\right) + x^{2} = 1$"
],
@@ -402,7 +402,7 @@
"outputs": [
{
"data": {
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+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle \\left[ - x - 6 + \\frac{1}{x^{2}}\\right]$"
],
@@ -436,7 +436,7 @@
"outputs": [
{
"data": {
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+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAKoAAAAYCAYAAABqdGb8AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAFRElEQVRoBe2b63HUMBDHDyYFAKmA0AGPDpIOklBBoAMYvuVbBjoIVACkg4QK8ugAOoC5DsL/ZySNzpb8kGXd3eCd0UnW8+/d1e5KTh7c398vhtLp6ekjjflgxu2Z/ET1y6Fzzf1nDlgOtOnVju00MP+oSd/aMSqfq3yr9MzWzfnMgQQORPXqYcJkDHkj5dz3xn5UeU91z726uThzYCgHonqVqqhY05uhKOr9pdg2bKg3zc8jOLDFfI3qVZKiihGflfx4lAV+qe6uL3/V9536zha4L8NMP/GtwTPVPVLyNz3eDf5uFQlzVK9SY1THAE0O4w6VXrjKjoLG0H9X+aeOrnNzkwM/xDcOs9YoUIYc/9V+pfRcCVf6+V/zdv2CX4idXiVZVPvKmoxdTHz6QmXfwtoujVz9YOwH5e8bjXNFHw78USd4jSDh5YVSg//iL0bgreG3ittDwtzQq2SLaiZ7r/wAFphn8l8dLEGxuSUoQsLDoQ9XuBGWJQOeO81x1JN58Bl+uxuanuNctwx43Vx9CloPJW3oVZJFNZPBhHOVcTHsbiwku72LjtW/pNJgdUibQsXwGD7D7zHvXxIvShrUq1SLyp0pL0DuSAxp3blqJ+bosrhuvrmQhQPw+1ippHFIBR7VK6eoZte9MSu8Un6ihIa/NnXX6kM8tFD+2NQNzQgTrmKDhmCIzZGz3sPDh4xbPTthm7Yvyvu64WzQtCZywlDsKiGjM9XZw5UeVwh+w3eHfaV14gfDp9F65bt+vgp8Ign7tdIXpX0949JhCrHOWHqpCX62TFICQ8vyjSYOffDjUqn+/lgpPERpQhbfjKyQDYlNRCweIviNMq+Lssi0UlS9JBrvC2KpZ4Rgd+GTWrsekwgmB+PYghh6ARce4m42LIRFquNu9Q7VqAl+hOtACflUpDKuHasZO6CCey2KKmzZ9Mq6/hvzwtXL64c7OU6XFUOU53JvKLxjsl3M5KMwCCOCClkV1lyoPRQ/t52g/Q8YWM8z5vGItep1rnkCPG7uQAFlxftxu1E/A/CMgWilifCOkqkPuFJUgazHNyHB+OOyl8di0PiQIi5Uj2dAgIM+Lqi/3aQoJIK23oU5sbbUtcXbWfFoLdYlBHmi3F3uU+9RSCHbjIMbqjmnwJtNryrX79CqIMBWMNXBiTbV8YkuxAR/aJ8ybqhznokx9MHp98GbOO9iGuDRUjjrgvDHTVEmxg/xz3qNEB76w/e10liZ7hgF/K63IOjFQrCzEILvQnJ9SWLORrxUGIMgDCLw+rxg8FriU63Lt3AOT3Vi48SsO0pcx18fn/05t0yxqLwk6Y+ZfGX3qY42e6hQcRSx47n6qlNJDPW1u55XhGz4AV7ccGniA8vKoUnP7wyI2DmiOm+UBqr1ssp0RxOyE4m/mHihF+f78KUSDOECFgV2YQB9RtBXjcV616kkhvraXc9YMO5LuRX5rWT/ODxmwbrmS24XBg54eD6rrFhLDMtT1S0jEyPXYPwZ6Z+rOqtMH6T8K8qYNxFDudc7Uo51nZy0TtJhKgZM86Gw+8pjB5rY0Ko+N562xbQWYQtGx26utu7BtpJ4gwBMJa6/NCHokjscSxOzNq3vLiFhvdxnYpU5mHA3eNY6sL0xGU/7tMFWvAH8HkMl8UZxFreoIJHAie8IMVbivyjKNTUIH9afuLC62lJO2IL7DR1o1oQyvKwwYk3BzsFv64kYdR1E4I/QN52JKCT3lhxYcJ8IvnhsqnVTiDi2pOdKwdh7zFosKugkcHb8ofJBF/G93+w/7iiesrEulG+0xxoior/cLWUUiDm0fAAAAABJRU5ErkJggg==\n",
"text/latex": [
"$\\displaystyle x^{2} \\left(x + y + 5\\right) + x^{2}$"
],
@@ -468,52 +468,52 @@
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" -->\n",
"<!-- Title: %3 Pages: 1 -->\n",
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- " viewBox=\"0.00 0.00 422.00 260.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
+ "<svg width=\"426pt\" height=\"260pt\"\n",
+ " viewBox=\"0.00 0.00 426.00 260.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
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"<title>%3</title>\n",
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- "<!-- Add(Pow(Symbol(x), Integer(2)), Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y))))_() -->\n",
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+ "<!-- Add(Pow(Symbol('x'), Integer(2)), Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y'))))_() -->\n",
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- "<text text-anchor=\"middle\" x=\"135\" y=\"-230.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Add</text>\n",
+ "<title>Add(Pow(Symbol('x'), Integer(2)), Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y'))))_()</title>\n",
+ "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"136\" cy=\"-234\" rx=\"29.4969\" ry=\"18\"/>\n",
+ "<text text-anchor=\"middle\" x=\"136\" y=\"-230.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Add</text>\n",
"</g>\n",
- "<!-- Pow(Symbol(x), Integer(2))_(0,) -->\n",
+ "<!-- Pow(Symbol('x'), Integer(2))_(0,) -->\n",
"<g id=\"node2\" class=\"node\">\n",
- "<title>Pow(Symbol(x), Integer(2))_(0,)</title>\n",
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- "<text text-anchor=\"middle\" x=\"99\" y=\"-158.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Pow</text>\n",
+ "<title>Pow(Symbol('x'), Integer(2))_(0,)</title>\n",
+ "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"98\" cy=\"-162\" rx=\"30.5947\" ry=\"18\"/>\n",
+ "<text text-anchor=\"middle\" x=\"98\" y=\"-158.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Pow</text>\n",
"</g>\n",
- "<!-- Add(Pow(Symbol(x), Integer(2)), Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y))))_()->Pow(Symbol(x), Integer(2))_(0,) -->\n",
+ "<!-- Add(Pow(Symbol('x'), Integer(2)), Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y'))))_()->Pow(Symbol('x'), Integer(2))_(0,) -->\n",
"<g id=\"edge1\" class=\"edge\">\n",
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- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"115.237,-186.6477 107.6343,-179.2687 108.976,-189.7782 115.237,-186.6477\"/>\n",
+ "<title>Add(Pow(Symbol('x'), Integer(2)), Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y'))))_()->Pow(Symbol('x'), Integer(2))_(0,)</title>\n",
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"</g>\n",
- "<!-- Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,) -->\n",
+ "<!-- Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y')))_(1,) -->\n",
"<g id=\"node5\" class=\"node\">\n",
- "<title>Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)</title>\n",
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- "<text text-anchor=\"middle\" x=\"171\" y=\"-158.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Mul</text>\n",
+ "<title>Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y')))_(1,)</title>\n",
+ "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"175\" cy=\"-162\" rx=\"28.6953\" ry=\"18\"/>\n",
+ "<text text-anchor=\"middle\" x=\"175\" y=\"-158.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Mul</text>\n",
"</g>\n",
- "<!-- Add(Pow(Symbol(x), Integer(2)), Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y))))_()->Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,) -->\n",
+ "<!-- Add(Pow(Symbol('x'), Integer(2)), Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y'))))_()->Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y')))_(1,) -->\n",
"<g id=\"edge2\" class=\"edge\">\n",
- "<title>Add(Pow(Symbol(x), Integer(2)), Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y))))_()->Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)</title>\n",
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- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"161.024,-189.7782 162.3657,-179.2687 154.763,-186.6477 161.024,-189.7782\"/>\n",
+ "<title>Add(Pow(Symbol('x'), Integer(2)), Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y'))))_()->Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y')))_(1,)</title>\n",
+ "<path fill=\"none\" stroke=\"#000000\" d=\"M145.4408,-216.5708C150.0396,-208.0807 155.6664,-197.6929 160.7718,-188.2674\"/>\n",
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"</g>\n",
- "<!-- Symbol(x)_(0, 0) -->\n",
+ "<!-- Symbol('x')_(0, 0) -->\n",
"<g id=\"node3\" class=\"node\">\n",
- "<title>Symbol(x)_(0, 0)</title>\n",
+ "<title>Symbol('x')_(0, 0)</title>\n",
"<ellipse fill=\"none\" stroke=\"#000000\" cx=\"27\" cy=\"-90\" rx=\"27\" ry=\"18\"/>\n",
"<text text-anchor=\"middle\" x=\"27\" y=\"-86.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">x</text>\n",
"</g>\n",
- "<!-- Pow(Symbol(x), Integer(2))_(0,)->Symbol(x)_(0, 0) -->\n",
+ "<!-- Pow(Symbol('x'), Integer(2))_(0,)->Symbol('x')_(0, 0) -->\n",
"<g id=\"edge3\" class=\"edge\">\n",
- "<title>Pow(Symbol(x), Integer(2))_(0,)->Symbol(x)_(0, 0)</title>\n",
- "<path fill=\"none\" stroke=\"#000000\" d=\"M83.7307,-146.7307C73.803,-136.803 60.6847,-123.6847 49.5637,-112.5637\"/>\n",
- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"51.7933,-109.8436 42.2473,-105.2473 46.8436,-114.7933 51.7933,-109.8436\"/>\n",
+ "<title>Pow(Symbol('x'), Integer(2))_(0,)->Symbol('x')_(0, 0)</title>\n",
+ "<path fill=\"none\" stroke=\"#000000\" d=\"M82.5941,-146.3771C72.7854,-136.4302 59.9251,-123.3888 49.0442,-112.3547\"/>\n",
+ "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"51.4029,-109.7619 41.8893,-105.099 46.4187,-114.6769 51.4029,-109.7619\"/>\n",
"</g>\n",
"<!-- Integer(2)_(0, 1) -->\n",
"<g id=\"node4\" class=\"node\">\n",
@@ -521,101 +521,101 @@
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"<text text-anchor=\"middle\" x=\"99\" y=\"-86.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">2</text>\n",
"</g>\n",
- "<!-- Pow(Symbol(x), Integer(2))_(0,)->Integer(2)_(0, 1) -->\n",
+ "<!-- Pow(Symbol('x'), Integer(2))_(0,)->Integer(2)_(0, 1) -->\n",
"<g id=\"edge4\" class=\"edge\">\n",
- "<title>Pow(Symbol(x), Integer(2))_(0,)->Integer(2)_(0, 1)</title>\n",
- "<path fill=\"none\" stroke=\"#000000\" d=\"M99,-143.8314C99,-136.131 99,-126.9743 99,-118.4166\"/>\n",
- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"102.5001,-118.4132 99,-108.4133 95.5001,-118.4133 102.5001,-118.4132\"/>\n",
+ "<title>Pow(Symbol('x'), Integer(2))_(0,)->Integer(2)_(0, 1)</title>\n",
+ "<path fill=\"none\" stroke=\"#000000\" d=\"M98.2523,-143.8314C98.3593,-136.131 98.4865,-126.9743 98.6053,-118.4166\"/>\n",
+ "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"102.1049,-118.4609 98.7443,-108.4133 95.1056,-118.3637 102.1049,-118.4609\"/>\n",
"</g>\n",
- "<!-- Pow(Symbol(x), Integer(2))_(1, 0) -->\n",
+ "<!-- Pow(Symbol('x'), Integer(2))_(1, 0) -->\n",
"<g id=\"node6\" class=\"node\">\n",
- "<title>Pow(Symbol(x), Integer(2))_(1, 0)</title>\n",
- "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"171\" cy=\"-90\" rx=\"27\" ry=\"18\"/>\n",
- "<text text-anchor=\"middle\" x=\"171\" y=\"-86.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Pow</text>\n",
+ "<title>Pow(Symbol('x'), Integer(2))_(1, 0)</title>\n",
+ "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"175\" cy=\"-90\" rx=\"30.5947\" ry=\"18\"/>\n",
+ "<text text-anchor=\"middle\" x=\"175\" y=\"-86.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Pow</text>\n",
"</g>\n",
- "<!-- Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)->Pow(Symbol(x), Integer(2))_(1, 0) -->\n",
+ "<!-- Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y')))_(1,)->Pow(Symbol('x'), Integer(2))_(1, 0) -->\n",
"<g id=\"edge5\" class=\"edge\">\n",
- "<title>Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)->Pow(Symbol(x), Integer(2))_(1, 0)</title>\n",
- "<path fill=\"none\" stroke=\"#000000\" d=\"M171,-143.8314C171,-136.131 171,-126.9743 171,-118.4166\"/>\n",
- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"174.5001,-118.4132 171,-108.4133 167.5001,-118.4133 174.5001,-118.4132\"/>\n",
+ "<title>Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y')))_(1,)->Pow(Symbol('x'), Integer(2))_(1, 0)</title>\n",
+ "<path fill=\"none\" stroke=\"#000000\" d=\"M175,-143.8314C175,-136.131 175,-126.9743 175,-118.4166\"/>\n",
+ "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"178.5001,-118.4132 175,-108.4133 171.5001,-118.4133 178.5001,-118.4132\"/>\n",
"</g>\n",
- "<!-- Add(Integer(5), Symbol(x), Symbol(y))_(1, 1) -->\n",
+ "<!-- Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1) -->\n",
"<g id=\"node9\" class=\"node\">\n",
- "<title>Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)</title>\n",
- "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"279\" cy=\"-90\" rx=\"27\" ry=\"18\"/>\n",
- "<text text-anchor=\"middle\" x=\"279\" y=\"-86.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Add</text>\n",
+ "<title>Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1)</title>\n",
+ "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"286\" cy=\"-90\" rx=\"29.4969\" ry=\"18\"/>\n",
+ "<text text-anchor=\"middle\" x=\"286\" y=\"-86.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">Add</text>\n",
"</g>\n",
- "<!-- Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)->Add(Integer(5), Symbol(x), Symbol(y))_(1, 1) -->\n",
+ "<!-- Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y')))_(1,)->Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1) -->\n",
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- "<title>Mul(Pow(Symbol(x), Integer(2)), Add(Integer(5), Symbol(x), Symbol(y)))_(1,)->Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)</title>\n",
- "<path fill=\"none\" stroke=\"#000000\" d=\"M190.3082,-149.1278C207.3555,-137.763 232.4019,-121.0654 251.5344,-108.3104\"/>\n",
- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"253.4799,-111.2199 259.8589,-102.7607 249.5969,-105.3956 253.4799,-111.2199\"/>\n",
+ "<title>Mul(Pow(Symbol('x'), Integer(2)), Add(Integer(5), Symbol('x'), Symbol('y')))_(1,)->Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1)</title>\n",
+ "<path fill=\"none\" stroke=\"#000000\" d=\"M195.1013,-148.9613C212.438,-137.7159 237.684,-121.3401 257.173,-108.6986\"/>\n",
+ "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"259.1882,-111.5633 265.6732,-103.185 255.3789,-105.6905 259.1882,-111.5633\"/>\n",
"</g>\n",
- "<!-- Symbol(x)_(1, 0, 0) -->\n",
+ "<!-- Symbol('x')_(1, 0, 0) -->\n",
"<g id=\"node7\" class=\"node\">\n",
- "<title>Symbol(x)_(1, 0, 0)</title>\n",
- "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"99\" cy=\"-18\" rx=\"27\" ry=\"18\"/>\n",
- "<text text-anchor=\"middle\" x=\"99\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">x</text>\n",
+ "<title>Symbol('x')_(1, 0, 0)</title>\n",
+ "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"103\" cy=\"-18\" rx=\"27\" ry=\"18\"/>\n",
+ "<text text-anchor=\"middle\" x=\"103\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">x</text>\n",
"</g>\n",
- "<!-- Pow(Symbol(x), Integer(2))_(1, 0)->Symbol(x)_(1, 0, 0) -->\n",
+ "<!-- Pow(Symbol('x'), Integer(2))_(1, 0)->Symbol('x')_(1, 0, 0) -->\n",
"<g id=\"edge7\" class=\"edge\">\n",
- "<title>Pow(Symbol(x), Integer(2))_(1, 0)->Symbol(x)_(1, 0, 0)</title>\n",
- "<path fill=\"none\" stroke=\"#000000\" d=\"M155.7307,-74.7307C145.803,-64.803 132.6847,-51.6847 121.5637,-40.5637\"/>\n",
- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"123.7933,-37.8436 114.2473,-33.2473 118.8436,-42.7933 123.7933,-37.8436\"/>\n",
+ "<title>Pow(Symbol('x'), Integer(2))_(1, 0)->Symbol('x')_(1, 0, 0)</title>\n",
+ "<path fill=\"none\" stroke=\"#000000\" d=\"M159.3771,-74.3771C149.4302,-64.4302 136.3888,-51.3888 125.3547,-40.3547\"/>\n",
+ "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"127.645,-37.6953 118.099,-33.099 122.6953,-42.645 127.645,-37.6953\"/>\n",
"</g>\n",
"<!-- Integer(2)_(1, 0, 1) -->\n",
"<g id=\"node8\" class=\"node\">\n",
"<title>Integer(2)_(1, 0, 1)</title>\n",
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- "<text text-anchor=\"middle\" x=\"171\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">2</text>\n",
+ "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"175\" cy=\"-18\" rx=\"27\" ry=\"18\"/>\n",
+ "<text text-anchor=\"middle\" x=\"175\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">2</text>\n",
"</g>\n",
- "<!-- Pow(Symbol(x), Integer(2))_(1, 0)->Integer(2)_(1, 0, 1) -->\n",
+ "<!-- Pow(Symbol('x'), Integer(2))_(1, 0)->Integer(2)_(1, 0, 1) -->\n",
"<g id=\"edge8\" class=\"edge\">\n",
- "<title>Pow(Symbol(x), Integer(2))_(1, 0)->Integer(2)_(1, 0, 1)</title>\n",
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- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"174.5001,-46.4132 171,-36.4133 167.5001,-46.4133 174.5001,-46.4132\"/>\n",
+ "<title>Pow(Symbol('x'), Integer(2))_(1, 0)->Integer(2)_(1, 0, 1)</title>\n",
+ "<path fill=\"none\" stroke=\"#000000\" d=\"M175,-71.8314C175,-64.131 175,-54.9743 175,-46.4166\"/>\n",
+ "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"178.5001,-46.4132 175,-36.4133 171.5001,-46.4133 178.5001,-46.4132\"/>\n",
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"<!-- Integer(5)_(1, 1, 0) -->\n",
"<g id=\"node10\" class=\"node\">\n",
"<title>Integer(5)_(1, 1, 0)</title>\n",
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- "<text text-anchor=\"middle\" x=\"243\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">5</text>\n",
+ "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"247\" cy=\"-18\" rx=\"27\" ry=\"18\"/>\n",
+ "<text text-anchor=\"middle\" x=\"247\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">5</text>\n",
"</g>\n",
- "<!-- Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)->Integer(5)_(1, 1, 0) -->\n",
+ "<!-- Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1)->Integer(5)_(1, 1, 0) -->\n",
"<g id=\"edge9\" class=\"edge\">\n",
- "<title>Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)->Integer(5)_(1, 1, 0)</title>\n",
- "<path fill=\"none\" stroke=\"#000000\" d=\"M270.2854,-72.5708C266.0403,-64.0807 260.8464,-53.6929 256.1337,-44.2674\"/>\n",
- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"259.237,-42.6477 251.6343,-35.2687 252.976,-45.7782 259.237,-42.6477\"/>\n",
+ "<title>Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1)->Integer(5)_(1, 1, 0)</title>\n",
+ "<path fill=\"none\" stroke=\"#000000\" d=\"M276.5592,-72.5708C271.9604,-64.0807 266.3336,-53.6929 261.2282,-44.2674\"/>\n",
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"</g>\n",
- "<!-- Symbol(x)_(1, 1, 1) -->\n",
+ "<!-- Symbol('x')_(1, 1, 1) -->\n",
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- "<title>Symbol(x)_(1, 1, 1)</title>\n",
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- "<text text-anchor=\"middle\" x=\"315\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">x</text>\n",
+ "<title>Symbol('x')_(1, 1, 1)</title>\n",
+ "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"319\" cy=\"-18\" rx=\"27\" ry=\"18\"/>\n",
+ "<text text-anchor=\"middle\" x=\"319\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">x</text>\n",
"</g>\n",
- "<!-- Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)->Symbol(x)_(1, 1, 1) -->\n",
+ "<!-- Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1)->Symbol('x')_(1, 1, 1) -->\n",
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- "<title>Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)->Symbol(x)_(1, 1, 1)</title>\n",
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- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"305.024,-45.7782 306.3657,-35.2687 298.763,-42.6477 305.024,-45.7782\"/>\n",
+ "<title>Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1)->Symbol('x')_(1, 1, 1)</title>\n",
+ "<path fill=\"none\" stroke=\"#000000\" d=\"M293.9884,-72.5708C297.8392,-64.1691 302.5417,-53.9091 306.8256,-44.5623\"/>\n",
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- "<!-- Symbol(y)_(1, 1, 2) -->\n",
+ "<!-- Symbol('y')_(1, 1, 2) -->\n",
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- "<title>Symbol(y)_(1, 1, 2)</title>\n",
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- "<text text-anchor=\"middle\" x=\"387\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">y</text>\n",
+ "<title>Symbol('y')_(1, 1, 2)</title>\n",
+ "<ellipse fill=\"none\" stroke=\"#000000\" cx=\"391\" cy=\"-18\" rx=\"27\" ry=\"18\"/>\n",
+ "<text text-anchor=\"middle\" x=\"391\" y=\"-14.3\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">y</text>\n",
"</g>\n",
- "<!-- Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)->Symbol(y)_(1, 1, 2) -->\n",
+ "<!-- Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1)->Symbol('y')_(1, 1, 2) -->\n",
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- "<title>Add(Integer(5), Symbol(x), Symbol(y))_(1, 1)->Symbol(y)_(1, 1, 2)</title>\n",
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- "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"361.4799,-39.2199 367.8589,-30.7607 357.5969,-33.3956 361.4799,-39.2199\"/>\n",
+ "<title>Add(Integer(5), Symbol('x'), Symbol('y'))_(1, 1)->Symbol('y')_(1, 1, 2)</title>\n",
+ "<path fill=\"none\" stroke=\"#000000\" d=\"M305.7497,-76.4574C322.0864,-65.2551 345.4675,-49.2223 363.6128,-36.7798\"/>\n",
+ "<polygon fill=\"#000000\" stroke=\"#000000\" points=\"365.7782,-39.5388 372.0461,-30.997 361.8194,-33.7657 365.7782,-39.5388\"/>\n",
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"</svg>\n"
],
"text/plain": [
- "<graphviz.files.Source at 0x7ff8a018e7f0>"
+ "<graphviz.files.Source at 0x7f9701574250>"
]
},
"execution_count": 19,
@@ -662,7 +662,7 @@
"outputs": [
{
"data": {
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+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle \\left( x^{2}, \\ x^{2} \\left(x + y + 5\\right)\\right)$"
],
@@ -719,7 +719,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle {{f}_{(1,0)}^{1}}$"
],
@@ -789,16 +789,16 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": "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\n",
"text/latex": [
- "$\\displaystyle \\left(- {{img}_{(-1,-1)}^{2}} w_{1} - {{img}_{(-1,0)}^{2}} w_{2} - {{img}_{(-1,1)}^{2}} w_{1} + {{img}_{(1,-1)}^{2}} w_{1} + {{img}_{(1,0)}^{2}} w_{2} - {{img}_{(1,1)}^{2}} w_{1}\\right)^{2}$"
+ "$\\displaystyle \\left({{img}_{(1,0)}^{2}} w_{2} - {{img}_{(1,1)}^{2}} w_{1} - {{img}_{(-1,1)}^{2}} w_{1} + {{img}_{(1,-1)}^{2}} w_{1} - {{img}_{(-1,-1)}^{2}} w_{1} - {{img}_{(-1,0)}^{2}} w_{2}\\right)^{2}$"
],
"text/plain": [
" \n",
- "(-img_SW__2â‹…wâ‚ - img_W__2â‹…wâ‚‚ - img_NW__2â‹…wâ‚ + img_SE__2â‹…wâ‚ + img_E__2â‹…wâ‚‚ - img\n",
+ "(img_E__2â‹…wâ‚‚ - img_NE__2â‹…wâ‚ - img_NW__2â‹…wâ‚ + img_SE__2â‹…wâ‚ - img_SW__2â‹…wâ‚ - img\n",
"\n",
- " 2\n",
- "_NE__2â‹…wâ‚) "
+ " 2\n",
+ "_W__2â‹…wâ‚‚) "
]
},
"execution_count": 26,
@@ -828,16 +828,16 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": "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\n",
"text/latex": [
- "$\\displaystyle \\left(- 0.5 {{img}_{(-1,-1)}^{2}} - {{img}_{(-1,0)}^{2}} w_{2} - 0.5 {{img}_{(-1,1)}^{2}} + 0.5 {{img}_{(1,-1)}^{2}} + {{img}_{(1,0)}^{2}} w_{2} - 0.5 {{img}_{(1,1)}^{2}}\\right)^{2}$"
+ "$\\displaystyle \\left({{img}_{(1,0)}^{2}} w_{2} - 0.5 {{img}_{(1,1)}^{2}} - 0.5 {{img}_{(-1,1)}^{2}} + 0.5 {{img}_{(1,-1)}^{2}} - 0.5 {{img}_{(-1,-1)}^{2}} - {{img}_{(-1,0)}^{2}} w_{2}\\right)^{2}$"
],
"text/plain": [
" \n",
- "(-0.5â‹…img_SW__2 - img_W__2â‹…wâ‚‚ - 0.5â‹…img_NW__2 + 0.5â‹…img_SE__2 + img_E__2â‹…wâ‚‚ - \n",
+ "(img_E__2â‹…wâ‚‚ - 0.5â‹…img_NE__2 - 0.5â‹…img_NW__2 + 0.5â‹…img_SE__2 - 0.5â‹…img_SW__2 -\n",
"\n",
- " 2\n",
- "0.5â‹…img_NE__2) "
+ " 2\n",
+ " img_W__2â‹…wâ‚‚) "
]
},
"execution_count": 27,
@@ -864,16 +864,16 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": "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\n",
"text/latex": [
- "$\\displaystyle {{dst}_{(0,0)}} \\leftarrow \\left(- 0.5 {{img}_{(-1,-1)}^{2}} - {{img}_{(-1,0)}^{2}} w_{2} - 0.5 {{img}_{(-1,1)}^{2}} + 0.5 {{img}_{(1,-1)}^{2}} + {{img}_{(1,0)}^{2}} w_{2} - 0.5 {{img}_{(1,1)}^{2}}\\right)^{2}$"
+ "$\\displaystyle {{dst}_{(0,0)}} \\leftarrow \\left({{img}_{(1,0)}^{2}} w_{2} - 0.5 {{img}_{(1,1)}^{2}} - 0.5 {{img}_{(-1,1)}^{2}} + 0.5 {{img}_{(1,-1)}^{2}} - 0.5 {{img}_{(-1,-1)}^{2}} - {{img}_{(-1,0)}^{2}} w_{2}\\right)^{2}$"
],
"text/plain": [
" \n",
- "dst_C := (-0.5â‹…img_SW__2 - img_W__2â‹…wâ‚‚ - 0.5â‹…img_NW__2 + 0.5â‹…img_SE__2 + img_E\n",
+ "dst_C := (img_E__2â‹…wâ‚‚ - 0.5â‹…img_NE__2 - 0.5â‹…img_NW__2 + 0.5â‹…img_SE__2 - 0.5â‹…im\n",
"\n",
- " 2\n",
- "__2â‹…wâ‚‚ - 0.5â‹…img_NE__2) "
+ " 2\n",
+ "g_SW__2 - img_W__2â‹…wâ‚‚) "
]
},
"execution_count": 28,
@@ -915,12 +915,12 @@
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 1152x432 with 1 Axes>"
]
@@ -937,7 +937,7 @@
" import imageio\n",
" from io import BytesIO\n",
"\n",
- " response = requests.get(\"https://www.python.org/static/img/python-logo.png\")\n",
+ " response = requests.get(\"https://www.python.org/static/community_logos/python-logo-master-v3-TM.png\")\n",
" img = imageio.imread(BytesIO(response.content)).astype(np.double)\n",
" img /= img.max()\n",
" plt.imshow(img);\n",
@@ -948,12 +948,12 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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@@ -1238,12 +1238,12 @@
"text/html": [
"<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_dst</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_img</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_size_dst_0</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_size_dst_1</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_dst_0</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_dst_1</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_img_0</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">,</span> <span class=\"kt\">int64_t</span> <span class=\"k\">const</span> <span class=\"n\">_stride_img_2</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"n\">w_2</span><span class=\"p\">)</span>\n",
"<span class=\"p\">{</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_img_22</span> <span class=\"o\">=</span> <span class=\"n\">_data_img</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">_stride_img_2</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_img_22</span> <span class=\"o\">=</span> <span class=\"n\">_data_img</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">_stride_img_2</span><span class=\"p\">;</span>\n",
" <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\"><</span> <span class=\"n\">_size_dst_0</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
" <span class=\"p\">{</span>\n",
" <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_dst_00</span> <span class=\"o\">=</span> <span class=\"n\">_data_dst</span> <span class=\"o\">+</span> <span class=\"n\">_stride_dst_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_img_22_01</span> <span class=\"o\">=</span> <span class=\"n\">_stride_img_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_0</span> <span class=\"o\">+</span> <span class=\"n\">_data_img_22</span><span class=\"p\">;</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_img_22_0m1</span> <span class=\"o\">=</span> <span class=\"n\">_stride_img_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_0</span> <span class=\"o\">+</span> <span class=\"n\">_data_img_22</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_img_22_01</span> <span class=\"o\">=</span> <span class=\"n\">_stride_img_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_0</span> <span class=\"o\">+</span> <span class=\"n\">_data_img_22</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_img_22_0m1</span> <span class=\"o\">=</span> <span class=\"n\">_stride_img_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_0</span> <span class=\"o\">+</span> <span class=\"n\">_data_img_22</span><span class=\"p\">;</span>\n",
" <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\"><</span> <span class=\"n\">_size_dst_1</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
" <span class=\"p\">{</span>\n",
" <span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">_stride_dst_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"p\">((</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">])</span><span class=\"o\">*</span><span class=\"p\">(</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]));</span>\n",
@@ -1255,12 +1255,12 @@
"text/plain": [
"FUNC_PREFIX void kernel(double * RESTRICT _data_dst, double * RESTRICT const _data_img, int64_t const _size_dst_0, int64_t const _size_dst_1, int64_t const _stride_dst_0, int64_t const _stride_dst_1, int64_t const _stride_img_0, int64_t const _stride_img_1, int64_t const _stride_img_2, double w_2)\n",
"{\n",
- " double * RESTRICT const _data_img_22 = _data_img + 2*_stride_img_2;\n",
+ " double * RESTRICT _data_img_22 = _data_img + 2*_stride_img_2;\n",
" for (int ctr_0 = 1; ctr_0 < _size_dst_0 - 1; ctr_0 += 1)\n",
" {\n",
" double * RESTRICT _data_dst_00 = _data_dst + _stride_dst_0*ctr_0;\n",
- " double * RESTRICT const _data_img_22_01 = _stride_img_0*ctr_0 + _stride_img_0 + _data_img_22;\n",
- " double * RESTRICT const _data_img_22_0m1 = _stride_img_0*ctr_0 - _stride_img_0 + _data_img_22;\n",
+ " double * RESTRICT _data_img_22_01 = _stride_img_0*ctr_0 + _stride_img_0 + _data_img_22;\n",
+ " double * RESTRICT _data_img_22_0m1 = _stride_img_0*ctr_0 - _stride_img_0 + _data_img_22;\n",
" for (int ctr_1 = 1; ctr_1 < _size_dst_1 - 1; ctr_1 += 1)\n",
" {\n",
" _data_dst_00[_stride_dst_1*ctr_1] = ((w_2*_data_img_22_01[_stride_img_1*ctr_1] - w_2*_data_img_22_0m1[_stride_img_1*ctr_1] - 0.5*_data_img_22_01[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 - _stride_img_1] + 0.5*_data_img_22_01[_stride_img_1*ctr_1 - _stride_img_1])*(w_2*_data_img_22_01[_stride_img_1*ctr_1] - w_2*_data_img_22_0m1[_stride_img_1*ctr_1] - 0.5*_data_img_22_01[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 - _stride_img_1] + 0.5*_data_img_22_01[_stride_img_1*ctr_1 - _stride_img_1]));\n",
@@ -1269,9 +1269,8 @@
"}"
]
},
- "execution_count": 33,
"metadata": {},
- "output_type": "execute_result"
+ "output_type": "display_data"
}
],
"source": [
@@ -1377,13 +1376,13 @@
"<span class=\"p\">{</span>\n",
" <span class=\"cp\">#pragma omp parallel num_threads(2)</span>\n",
" <span class=\"p\">{</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_img_22</span> <span class=\"o\">=</span> <span class=\"n\">_data_img</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">_stride_img_2</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_img_22</span> <span class=\"o\">=</span> <span class=\"n\">_data_img</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">_stride_img_2</span><span class=\"p\">;</span>\n",
" <span class=\"cp\">#pragma omp for schedule(static)</span>\n",
" <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\"><</span> <span class=\"n\">_size_dst_0</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
" <span class=\"p\">{</span>\n",
" <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_dst_00</span> <span class=\"o\">=</span> <span class=\"n\">_data_dst</span> <span class=\"o\">+</span> <span class=\"n\">_stride_dst_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_img_22_01</span> <span class=\"o\">=</span> <span class=\"n\">_stride_img_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_0</span> <span class=\"o\">+</span> <span class=\"n\">_data_img_22</span><span class=\"p\">;</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_img_22_0m1</span> <span class=\"o\">=</span> <span class=\"n\">_stride_img_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_0</span> <span class=\"o\">+</span> <span class=\"n\">_data_img_22</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_img_22_01</span> <span class=\"o\">=</span> <span class=\"n\">_stride_img_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_0</span> <span class=\"o\">+</span> <span class=\"n\">_data_img_22</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_img_22_0m1</span> <span class=\"o\">=</span> <span class=\"n\">_stride_img_0</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_0</span> <span class=\"o\">+</span> <span class=\"n\">_data_img_22</span><span class=\"p\">;</span>\n",
" <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\"><</span> <span class=\"n\">_size_dst_1</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
" <span class=\"p\">{</span>\n",
" <span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">_stride_dst_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"p\">((</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">])</span><span class=\"o\">*</span><span class=\"p\">(</span><span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">w_2</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_0m1</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">0.5</span><span class=\"o\">*</span><span class=\"n\">_data_img_22_01</span><span class=\"p\">[</span><span class=\"n\">_stride_img_1</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"n\">_stride_img_1</span><span class=\"p\">]));</span>\n",
@@ -1398,13 +1397,13 @@
"{\n",
" #pragma omp parallel num_threads(2)\n",
" {\n",
- " double * RESTRICT const _data_img_22 = _data_img + 2*_stride_img_2;\n",
+ " double * RESTRICT _data_img_22 = _data_img + 2*_stride_img_2;\n",
" #pragma omp for schedule(static)\n",
" for (int ctr_0 = 1; ctr_0 < _size_dst_0 - 1; ctr_0 += 1)\n",
" {\n",
" double * RESTRICT _data_dst_00 = _data_dst + _stride_dst_0*ctr_0;\n",
- " double * RESTRICT const _data_img_22_01 = _stride_img_0*ctr_0 + _stride_img_0 + _data_img_22;\n",
- " double * RESTRICT const _data_img_22_0m1 = _stride_img_0*ctr_0 - _stride_img_0 + _data_img_22;\n",
+ " double * RESTRICT _data_img_22_01 = _stride_img_0*ctr_0 + _stride_img_0 + _data_img_22;\n",
+ " double * RESTRICT _data_img_22_0m1 = _stride_img_0*ctr_0 - _stride_img_0 + _data_img_22;\n",
" for (int ctr_1 = 1; ctr_1 < _size_dst_1 - 1; ctr_1 += 1)\n",
" {\n",
" _data_dst_00[_stride_dst_1*ctr_1] = ((w_2*_data_img_22_01[_stride_img_1*ctr_1] - w_2*_data_img_22_0m1[_stride_img_1*ctr_1] - 0.5*_data_img_22_01[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 - _stride_img_1] + 0.5*_data_img_22_01[_stride_img_1*ctr_1 - _stride_img_1])*(w_2*_data_img_22_01[_stride_img_1*ctr_1] - w_2*_data_img_22_0m1[_stride_img_1*ctr_1] - 0.5*_data_img_22_01[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 + _stride_img_1] - 0.5*_data_img_22_0m1[_stride_img_1*ctr_1 - _stride_img_1] + 0.5*_data_img_22_01[_stride_img_1*ctr_1 - _stride_img_1]));\n",
@@ -1414,9 +1413,8 @@
"}"
]
},
- "execution_count": 34,
"metadata": {},
- "output_type": "execute_result"
+ "output_type": "display_data"
}
],
"source": [
@@ -1548,15 +1546,15 @@
"text/html": [
"<div class=\"highlight\"><pre><span></span><span class=\"n\">FUNC_PREFIX</span> <span class=\"kt\">void</span> <span class=\"nf\">kernel</span><span class=\"p\">(</span><span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_I</span><span class=\"p\">,</span> <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_dst</span><span class=\"p\">)</span>\n",
"<span class=\"p\">{</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_I_21</span> <span class=\"o\">=</span> <span class=\"n\">_data_I</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_I_21</span> <span class=\"o\">=</span> <span class=\"n\">_data_I</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
" <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\"><</span> <span class=\"mi\">81</span><span class=\"p\">;</span> <span class=\"n\">ctr_0</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
" <span class=\"p\">{</span>\n",
" <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_dst_00</span> <span class=\"o\">=</span> <span class=\"n\">_data_dst</span> <span class=\"o\">+</span> <span class=\"mi\">290</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">;</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_I_21_01</span> <span class=\"o\">=</span> <span class=\"n\">_data_I_21</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">;</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_I_21_0m1</span> <span class=\"o\">=</span> <span class=\"n\">_data_I_21</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_I_21_01</span> <span class=\"o\">=</span> <span class=\"n\">_data_I_21</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_I_21_0m1</span> <span class=\"o\">=</span> <span class=\"n\">_data_I_21</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">;</span>\n",
" <span class=\"k\">for</span> <span class=\"p\">(</span><span class=\"kt\">int</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"mi\">1</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\"><</span> <span class=\"mi\">289</span><span class=\"p\">;</span> <span class=\"n\">ctr_1</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n",
" <span class=\"p\">{</span>\n",
- " <span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"o\">-</span><span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">4</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">4</span><span class=\"p\">];</span>\n",
+ " <span class=\"n\">_data_dst_00</span><span class=\"p\">[</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"o\">-</span><span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"n\">_data_I_21_01</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">4</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_21_0m1</span><span class=\"p\">[</span><span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">4</span><span class=\"p\">];</span>\n",
" <span class=\"p\">}</span>\n",
" <span class=\"p\">}</span>\n",
"<span class=\"p\">}</span>\n",
@@ -1565,23 +1563,22 @@
"text/plain": [
"FUNC_PREFIX void kernel(double * RESTRICT const _data_I, double * RESTRICT _data_dst)\n",
"{\n",
- " double * RESTRICT const _data_I_21 = _data_I + 1;\n",
+ " double * RESTRICT _data_I_21 = _data_I + 1;\n",
" for (int ctr_0 = 1; ctr_0 < 81; ctr_0 += 1)\n",
" {\n",
" double * RESTRICT _data_dst_00 = _data_dst + 290*ctr_0;\n",
- " double * RESTRICT const _data_I_21_01 = _data_I_21 + 1160*ctr_0 + 1160;\n",
- " double * RESTRICT const _data_I_21_0m1 = _data_I_21 + 1160*ctr_0 - 1160;\n",
+ " double * RESTRICT _data_I_21_01 = _data_I_21 + 1160*ctr_0 + 1160;\n",
+ " double * RESTRICT _data_I_21_0m1 = _data_I_21 + 1160*ctr_0 - 1160;\n",
" for (int ctr_1 = 1; ctr_1 < 289; ctr_1 += 1)\n",
" {\n",
- " _data_dst_00[ctr_1] = -2*_data_I_21_0m1[4*ctr_1] + 2*_data_I_21_01[4*ctr_1] - _data_I_21_01[4*ctr_1 + 4] + _data_I_21_01[4*ctr_1 - 4] - _data_I_21_0m1[4*ctr_1 + 4] - _data_I_21_0m1[4*ctr_1 - 4];\n",
+ " _data_dst_00[ctr_1] = -2.0*_data_I_21_0m1[4*ctr_1] + 2.0*_data_I_21_01[4*ctr_1] - _data_I_21_01[4*ctr_1 + 4] + _data_I_21_01[4*ctr_1 - 4] - _data_I_21_0m1[4*ctr_1 + 4] - _data_I_21_0m1[4*ctr_1 - 4];\n",
" }\n",
" }\n",
"}"
]
},
- "execution_count": 36,
"metadata": {},
- "output_type": "execute_result"
+ "output_type": "display_data"
}
],
"source": [
@@ -1716,10 +1713,10 @@
" <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">ctr_0</span> <span class=\"o\">=</span> <span class=\"n\">blockDim</span><span class=\"p\">.</span><span class=\"n\">x</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">x</span> <span class=\"o\">+</span> <span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">x</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
" <span class=\"k\">const</span> <span class=\"kt\">int64_t</span> <span class=\"n\">ctr_1</span> <span class=\"o\">=</span> <span class=\"n\">blockDim</span><span class=\"p\">.</span><span class=\"n\">y</span><span class=\"o\">*</span><span class=\"n\">blockIdx</span><span class=\"p\">.</span><span class=\"n\">y</span> <span class=\"o\">+</span> <span class=\"n\">threadIdx</span><span class=\"p\">.</span><span class=\"n\">y</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
" <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_dst_10</span> <span class=\"o\">=</span> <span class=\"n\">_data_dst</span> <span class=\"o\">+</span> <span class=\"n\">ctr_1</span><span class=\"p\">;</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_I_11_21</span> <span class=\"o\">=</span> <span class=\"n\">_data_I</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">5</span><span class=\"p\">;</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_I_1m1_21</span> <span class=\"o\">=</span> <span class=\"n\">_data_I</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">3</span><span class=\"p\">;</span>\n",
- " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"k\">const</span> <span class=\"n\">_data_I_10_21</span> <span class=\"o\">=</span> <span class=\"n\">_data_I</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
- " <span class=\"n\">_data_dst_10</span><span class=\"p\">[</span><span class=\"mi\">290</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"o\">-</span><span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">_data_I_10_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"o\">*</span><span class=\"n\">_data_I_10_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_11_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_11_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"n\">_data_I_1m1_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_1m1_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">];</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_I_11_21</span> <span class=\"o\">=</span> <span class=\"n\">_data_I</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">5</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_I_1m1_21</span> <span class=\"o\">=</span> <span class=\"n\">_data_I</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">-</span> <span class=\"mi\">3</span><span class=\"p\">;</span>\n",
+ " <span class=\"kt\">double</span> <span class=\"o\">*</span> <span class=\"n\">RESTRICT</span> <span class=\"n\">_data_I_10_21</span> <span class=\"o\">=</span> <span class=\"n\">_data_I</span> <span class=\"o\">+</span> <span class=\"mi\">4</span><span class=\"o\">*</span><span class=\"n\">ctr_1</span> <span class=\"o\">+</span> <span class=\"mi\">1</span><span class=\"p\">;</span>\n",
+ " <span class=\"n\">_data_dst_10</span><span class=\"p\">[</span><span class=\"mi\">290</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"o\">-</span><span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_10_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"mf\">2.0</span><span class=\"o\">*</span><span class=\"n\">_data_I_10_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_11_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_11_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">+</span> <span class=\"n\">_data_I_1m1_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">+</span> <span class=\"mi\">1160</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">_data_I_1m1_21</span><span class=\"p\">[</span><span class=\"mi\">1160</span><span class=\"o\">*</span><span class=\"n\">ctr_0</span> <span class=\"o\">-</span> <span class=\"mi\">1160</span><span class=\"p\">];</span>\n",
" <span class=\"p\">}</span> \n",
"<span class=\"p\">}</span>\n",
"</pre></div>\n"
@@ -1732,17 +1729,16 @@
" const int64_t ctr_0 = blockDim.x*blockIdx.x + threadIdx.x + 1;\n",
" const int64_t ctr_1 = blockDim.y*blockIdx.y + threadIdx.y + 1;\n",
" double * RESTRICT _data_dst_10 = _data_dst + ctr_1;\n",
- " double * RESTRICT const _data_I_11_21 = _data_I + 4*ctr_1 + 5;\n",
- " double * RESTRICT const _data_I_1m1_21 = _data_I + 4*ctr_1 - 3;\n",
- " double * RESTRICT const _data_I_10_21 = _data_I + 4*ctr_1 + 1;\n",
- " _data_dst_10[290*ctr_0] = -2*_data_I_10_21[1160*ctr_0 - 1160] + 2*_data_I_10_21[1160*ctr_0 + 1160] - _data_I_11_21[1160*ctr_0 + 1160] - _data_I_11_21[1160*ctr_0 - 1160] + _data_I_1m1_21[1160*ctr_0 + 1160] - _data_I_1m1_21[1160*ctr_0 - 1160];\n",
+ " double * RESTRICT _data_I_11_21 = _data_I + 4*ctr_1 + 5;\n",
+ " double * RESTRICT _data_I_1m1_21 = _data_I + 4*ctr_1 - 3;\n",
+ " double * RESTRICT _data_I_10_21 = _data_I + 4*ctr_1 + 1;\n",
+ " _data_dst_10[290*ctr_0] = -2.0*_data_I_10_21[1160*ctr_0 - 1160] + 2.0*_data_I_10_21[1160*ctr_0 + 1160] - _data_I_11_21[1160*ctr_0 + 1160] - _data_I_11_21[1160*ctr_0 - 1160] + _data_I_1m1_21[1160*ctr_0 + 1160] - _data_I_1m1_21[1160*ctr_0 - 1160];\n",
" } \n",
"}"
]
},
- "execution_count": 38,
"metadata": {},
- "output_type": "execute_result"
+ "output_type": "display_data"
}
],
"source": [
@@ -1767,7 +1763,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.8"
+ "version": "3.7.7"
}
},
"nbformat": 4,
diff --git a/doc/notebooks/04_tutorial_advection_diffusion.ipynb b/doc/notebooks/04_tutorial_advection_diffusion.ipynb
index 96b67539a..4d9cfbc8c 100644
--- a/doc/notebooks/04_tutorial_advection_diffusion.ipynb
+++ b/doc/notebooks/04_tutorial_advection_diffusion.ipynb
@@ -27,7 +27,7 @@
"outputs": [
{
"data": {
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+ "image/png": "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\n",
"text/latex": [
"$\\displaystyle \\nabla \\cdot(v c) - div(D \\nabla c) + \\partial_t c_{C}$"
],
@@ -72,13 +72,13 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
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\n",
"text/latex": [
- "$\\displaystyle 0.005 {{c}_{(-1,0)}} {{v}_{(-1,0)}} + 0.01 {{c}_{(-1,0)}} + 0.005 {{c}_{(0,-1)}} {{v}_{(0,-1)}^{1}} + 0.01 {{c}_{(0,-1)}} + 0.96 {{c}_{(0,0)}} - 0.005 {{c}_{(0,1)}} {{v}_{(0,1)}^{1}} + 0.01 {{c}_{(0,1)}} - 0.005 {{c}_{(1,0)}} {{v}_{(1,0)}} + 0.01 {{c}_{(1,0)}}$"
+ "$\\displaystyle 0.96 {{c}_{(0,0)}} - 0.005 {{c}_{(1,0)}} {{v}_{(1,0)}^{0}} + 0.01 {{c}_{(1,0)}} - 0.005 {{c}_{(0,1)}} {{v}_{(0,1)}^{1}} + 0.01 {{c}_{(0,1)}} + 0.005 {{c}_{(0,-1)}} {{v}_{(0,-1)}^{1}} + 0.01 {{c}_{(0,-1)}} + 0.005 {{c}_{(-1,0)}} {{v}_{(-1,0)}^{0}} + 0.01 {{c}_{(-1,0)}}$"
],
"text/plain": [
- "0.005â‹…c_Wâ‹…v_W__0 + 0.01â‹…c_W + 0.005â‹…c_Sâ‹…v_S__1 + 0.01â‹…c_S + 0.96â‹…c_C - 0.005â‹…c\n",
- "_Nâ‹…v_N__1 + 0.01â‹…c_N - 0.005â‹…c_Eâ‹…v_E__0 + 0.01â‹…c_E"
+ "0.96â‹…c_C - 0.005â‹…c_Eâ‹…v_E__0 + 0.01â‹…c_E - 0.005â‹…c_Nâ‹…v_N__1 + 0.01â‹…c_N + 0.005â‹…c\n",
+ "_Sâ‹…v_S__1 + 0.01â‹…c_S + 0.005â‹…c_Wâ‹…v_W__0 + 0.01â‹…c_W"
]
},
"execution_count": 3,
@@ -109,7 +109,7 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"<Figure size 1152x432 with 1 Axes>"
]
@@ -163,7 +163,7 @@
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VuWMjLb+NwludJv222//jHwucV+K9F0XgUZ0JF9vGYCR634iSX9trExFF3x//gwLv5ekX28YoK+WMh/bbptttEDjLHm7otDwUXLccS23ttttp6lrrrrrrrrrrrrrrrrrrrp4WZP/9ar1/xxEcBjhAY4rFxTrrvRAAET3gLAoUGZVFklWIcAEfHiHigACAFFADxQAMUDFYoN3FAxTFGKYUDAAEA0BgQKAIACQHAA8AAQCapA4B4AC1SVcWNyQAaoAJXaiABAAkyUgAFsofwGlYLUABCyGxgHRXQcJN8mEAAgi+CAuEDQskeULGYAJcrb+T8R27ULDcA9ZWnPsLo4APiIDmE8J063ajFzLIMhP/hAIG8QFAaAo950gccL0vWNSB8HKR8yfMhdQDmNEwA2BxNpkJ1X/wkEowMtF3xz9OOs4TMZ3YYBh/qWxQbu5YMVve78DgeYFmV8hU8kce2wh6WLUCR0DiA/ECQNvb9O+mLJAEjUPC1pHH+UzFqCsGgKoJPy+POSCQGDqkdi1CGD+EQq+mnskLCoshQOoGq0/xah4BPjTen4vAMbg5iiSC3t22/Dw4Yfe++/uZBfLbn7dbbJB1kEWoYAaVBPt0+LwhJ0GQB/22xZITaivb//GP8aUv35ffLyiF+25/n7f//0DCX+X5eRGtt7bdxcwzyb+22LlD7LIGdft/GP/kG97/uZPb8WoEtTiMjLp6X+PH6BX7kQq299xeDiZBFEPS/bb8f/yG77+9F060iEzUEwWhIBu5zBkPOnbbbbC6h8ZZf/9R5G02222mni0QOMtRtJp07eLUONI6N/pi1CL0EWW/2zqDp4kR5QcTIKCcXgP5yxkZbbe22VYzByeHYJCf2xaJbb7eyQeyCdQ00iIfFqHGWc/pJMmVCC4cmVJSFCr4zCQOvolVBDXXXXXXXXXXXXXXX/0/4UCkABNxEAAIAgA4u96JtNOF/GJnHXxSkNPadn//8IMfTwq9kcHPC7JHodXCHcv4knAahhNv79FSeMR7/7gAuQcsJep+U7UZUeBnOBM/VByoVospspcBigAGPsFPIOoP4ALJQYNTnTbyST99wDxBxBZy+IpGNai5A4KaUEK5j2xPCP8GGuoZp5uiz4Dj4AAIFgjWCcAn7vjEYAFXmABUKtAOKipfQfFCCFcEx+yqi0BSsdx2/xj8Y1igxRijFBi4pijFxWKMVisUxTFYuHOQUDGB5airyqVCoqiqQduF1AEgnGMUFBer3+93u4BIMBAX7OzqpCXIF1AKMNxkVf7+7xbAogPbbZy7lRagHHmKtDsD0H+NYtED5kQQ/p4tQOnMioTr+mmLU5FKqf4tCLH6eLINFBTHyGSGdqOsToh8iJk1x//5B53vv9yoqtfi0bakl+dFB14mi1H2TGn08WoPdEi009NNqJaMkLLQdEPlvHH/0YT3f3uOys5BGotCQddEbX7cWSGWWSr6f//9B2+9+iKTbaae1ZIfZaP//QMO/fTLt+yQe6C1D7LRH6fpJC1Cedwj/pp7UNMsyQ8I2sWocZZv0kFOSE86YiTolHzogZZZosgkHujf0FxH/+gYX+9AMPp9oQfBZBIaZYye350MtaEhwZDoU7RaHg907pp+cgovq0Xh//sEgQjdOkqCGuuuuuuuuuuuuuuuu+uunp4tGrf/HHEQhDQc3DGWUe0GW4LwCfrhdGAFQx+w4InVx+Tf+aBkgH9bvNwuoAUMOXwcOjXng754Q49ZrekeUrhUE4GRD+qVUru7hckBwaKMRO/vf7vchlBYAH8SUbhckA4zGGNP//xuNDb6SXiP/8mJfE/6qLqJ+rqkfpEwn///kxfVaqtVF6wWZfxJf//yBCuq11VUWnpE3//+Qbr9Y97KAgPpk1f//5B+tVVfXjBpJZM///0P1+1r4xXTJpN///o/qv6oIZ0alTRjYdHsTon8Wu3bb+N/4/QKxb9GK/TTGo3N+ni1+Omn7V2orOpyLTk0dnIcIroIjtoQ4lCRAkFMjoQwaRcY//IEhN/uyQLZ3AtTEjK+3zkEBxlusgkf8dQwDKMlrOhDxp0cQPHStZyQdeERkdGLh1Wjl51EjhEnIYd8dJyFCCap21MSOjBplushxDQ6EO0zFAovkSqgjrrrrrrrrrrrrrrr//+kEIUgANOcR4xZGHHT41sv8SQVXFAwWjVya37/grF8K/MTFFWgp3NPeUU/zyHDCE3kGGikVfEwQZN2RQAsxWr7oQwIIMneATKrYYUFTUC/ABeIc45PDy4hsnvh0V//h/UP09PXa9fxCEIQwIuM+8Y9zM3VaiJzrE1QajPqtHsJZECAT268KkMCWg2DkkpNJsUX5Nx2NKj9f5yCqrDGWVakYn/CqhTyUVJJJKl/MgUwiS6SWklSSS/CpLpUkkkkktJKlpkckJBIxNZII1lUCqkr0qSSXpcfGD//+QV369f//yLVfVfWo+nRr4//9GLX1rWWWVCFOjieVOiXnRbToivOqtOTedbTrYhkgk5L/S6SXFaa/EkEPEqEovKdbTk4oTIUV/6X8iSrFqFBXtP9rOSjTJojnUVsWs6itrW1shHOor9ZCuJV8p0R+iSdRKJ9OiuROA//2GxDt35WEHqvWtMP111111111111111/wh/w+FPoAJSHDAW2RuYWEI8a4cmwD/4e8ECkgsmXgQVqEFVO0vvGAYombrLEF+WcypEMOH//h4wt9Q3T09dc6MHfFb88wgnwjM3iax1zUxhrkJctFSv7awzhcCvSpey+RCCvze2GSEAhpDi97/9f09VGP6+Qt0aRa10bvpv/1+QTWqrqb9GGVdJL+k+lj4Kf28KkJ6X6XyJCKulpJJelS4sk3Mh36///6Cla1///yBXxhrXX//6BFrU6Hf//0CatebGD//+gSapSJOiGIKdNbW1tbW1tbXH//oFJe+9Ijo06Sotq5VEuNGLhyFacnRGvEWS6+23hkh3/9JL0f9vlW1iUZ3J1PjE5NrUuNZViVdolfTrqyX//+w2K5/3RN9lZVBDXXXXXXXXXXXXXXXXXXXT09ddcLogd9/T/wFtP//n88O5c+XEBemnb5jnMf+FCau/xOqwgHyDPcZWe5cwmoJyyC6emnpp6Ytp0E1CRCNv/vttkTMR//kPzd1/VF0LqAqowqqX+Yz+njuW29rx/jHxIIJXS/SR3/j/oV1rpSZnIIVOv+P9BsSvpUpkMVpJJW2///oERFkynTUNZZqjHqNd/+mntbW1tbW1tbW1OQWtraI7V2p8apD1f/bb229q7VyraEPH//khVHV9XEyO67qgh/t2ggzaszop6ciZJaNbRGjqfKhNHOS/220022002nIT///9hsRMvP+54OS+taYfrrrrrrrrrrrrrrrr+elEiz9hbABb6CQp6QxRwHgATAAloCjNpnYgXeuxT9p033ilRi7entQADFAyEP3GYZ0WSXe/7TSG5y5x2uAiICBTOwURNqEb7/h/QMA4IIApDAtKAfX6Z/4lDLaCh38PxDAGCHSQAXiETx7jxi7i56vfAE1MFRWa1ykJd7Q8QYiYiFBRSldf+/hKWD0wbO5reDxElg27ngeQUtra2tra/+IYBRAlwAEyIMr4wnLJSxy9jIRXMHV3nFueP/AAgGgQTAACoAgHiEth2traEI2tr//bCguJS8ABDUwVFVrXKQlnr4gxExEKCilK6/96dNbW0IGGTW1j0JAASbC32KUheYhdNPTT8AB8iDK6GE5ZKXODowSOFIFqURJHPa2tra2trj/2H0C2AAkRhFZDieshLnrLLRYjERzh1955bgcX229ra2tra8fx0xo8uUsABCU4RF5jXqSlnL4ghVzEqCylK7/9wa/ytbW1tbXH//ZAhwAEiMIrIcT1kJY9exGIjnDr7zy3Gtr4fABgGiNBB2trj/0D0CAIgAISnCIvMa9SUu5YNYghUzEqCylK7/9/a2tra2v/wwBgj8KtNwAXDFRpzzhqjqx6vfAGIwitjieshLHrDsRiI5w6+88lzwUKAQQYlcwTEKYYMVcwoRTDf/DH8IIcACmGGk88woks7fn/6Gobrrrrrrrrrrrrrrrrr+A+eXTC0ABEYbk1UI4W/Jo0TzRA1Gq7gf904AcMEJHEHFUC5bEM/4PxMGCdUaTdIurkPimfsZsAwcJjZEqrL/v/9IL0tLS0v7Kyeg6CgWAASIswADAYTGtPEPsP6BBGjdca38xOHG//54EKnuRdTsE6QpuhYBhWrGJpH9Olb/u8ZM0BBzlNEcfZ3HxMIyqhXIpyDJUGHWv/9BOAqAaQ5gAGOb9AUE7Y/4PwJ3UMa17NWPKycVD8yMwjwKzUGxRMBh0guKAAQtaWl//4QQUEcAkfr2gY0jTI6Eq///9TA+Ab9MJAAXmCcACQU00YcmRC+uEBAsnnA9HSxTHfZaDDLSon+G5Jr6I/zixgTLZjVzXLf+0giB8RSFshT3//X4SGMmLdN5Ev/3v/raYA1T5wHBdSNvMCgaxEJJSN2g/82Zn7Gqrb+GHSDYoABG1paWl/FSWmw6YYgAItPAAYBDY2GCkVG9ofQZDy9cU9zxCKAqSBNJmsTyIVp+EBpCkAAhi/oHDdcf9qgBDFY5OgvsYp/v/wJX4Qlb1asWRg0nAFDRDmKMmtYtPfD4hoZWchWcN61f//WmYRR1WguKf+/w/SDIaWlpaX+IfENBQMAAJgNAZrBiH3zSJi0wvzCCGiVHW9OLMa8K+DwQGDTk7C5iJagAXEgABADREQABQCaL33jYyqQZ3/pRwrynh1fQN1y6E+FAIAqqVJyXfBs/3sAAQA0VUBGARFtEwnvOigYJtJRckV9/v/40csE8xQ1zPc7Sz5SkPPnt7f/zZjf3urrf7uAgB01MKNX/3oP0gyKAAQtbW1/h/KKCgSgAOIlgBRxWNb6LbNG0OAAns2AECjr1uSJiPEMOgxFxMPLTN6CmASlZCQ+zkES+hkFGIe1mRffOIt/BbiJM2SfgFwdo+McNZQPUj90BEINYlpdkmQg5gon5+sAgEdeXIQlfHGYPCSZX8Orla94AxfJNyBeSi0K9fb8RiI/znZysR2/ozI7jiODD93kCgbJwRbCVrMfcrn6l9P3+8P0gyGlpaWl+FTOOL6YYgAJgNAZrBiH3zSJi0wvD2xg4QmrAtwhRAdXESDDCocorebMUvAZoBBTOpiBqsf29QBj+ivHmGbyZM2gAuJAACAGiIgACgE0Xvv2ogibGEchl972Z+x9Vv/8O6BjqX6E+AABADRVQEYBEW0TCe7p7ncWfGjlglmKGuZStDz57+78/8qKAHTUwo1f/eDDtBm1paX+YfuFBQLAAOTWAcQ/GtcPZJE3mAAuGRJllFgXxpHKI0yGAAvmwCHEVvIgyR8jYhFCvVxIkj1m+D+Isb80z6fyGUCIVlvE8Zww4d9QQNY15tsuSg9gx+wGAf+WSoEcjKD333gNBnlIWwwSra/n5MAQBCLy5DFL6D8AMfzT8ofs01KvyLoeGsN32ylf3//u8gIFOyaHETKTfh0Y+5yi3qbf3+//SC9LS0v//6CgqAIRFzsR0HV+AAkZENFIVHE9KPh4kCviG66YQAFADx6IFUYt9l6aAn7EM+TyhadEnFPUjYALDJGz7JDNPH/drEDDXU05clKNz9woCAdVKkxLvguf7gAA91QMoFRX+S/m7RQMNtJ65IrZ/f+LTlgrnCW39/fcAP+3gFBcyLzzHyCO3bKcc5wYfmzM/Y1Vb/dwQDpKQUSr3vQf0/l/h4ba6NEOKiOd04aWscfF//9/UfXXXXXXXXXXXXXXXXXXXXXXXXXfXXXXXfXXXXXXXXXXXXfXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXgAAAAeZBmjgX4BMuhmonozxPVr6tCwpYfeEavIvk7K+r5NXkeLrVmcfiOPkBF11jFED2ow/4iPFBH6hiu3DWQYiFp6DAv/6O5l//jOtcRsYpejcoxSkHNfXNGiCCHBC8Qeop8U63FRFDzpEQhxC1JlyeEkM9OMX6CPJNb8TUR4w9xHxNYnxM+JuCD4RQlOuWdwjEwQQhQj0i79K8/R2/J1Y8osu01tNRC2t6pzr/FeEfEy4lGeurw71qaq5T6X9KuNxfi5veJ8T4U8KaeHcQsF0NBLoISrQQl1LivFeEvFeEfE+JvFQVRLkWMxEXk9UEb8ViodiavC66jsV4qsbW4b5OquFK0iW1Rii5faJ1dFc8uMRLkwhaGS0sIQQqbw/CmIxKv6Wo7VWojJflL/9w3zd3M9eI8R4hb+a0haV2tSQz4hSxCk5e7nQIRHO/gghDxHvV0IcvmKu7vEQ7g28Z0RuBwqjuMIa/Ji4vFDEWkS6v9WIIOtfVpLcgxE+IsQrm61N0VqXFq5wx8lruxRMPwr42tfWu61XWvq8g5d66I8IL/PWdX19YxCH9oTfxiv5MQv17xi38YrwQ3R2iRiNTomaIxCv5PJ5KyK55KxXk/LkRHxBPi4INU/h3F+WCv8uGeYnAGD/+Pj74B3wAAAD5QZpUBfgFVHILegn9HahikznSX6sYxQH05EF4SNH/fERQXKtartd0MRi09BgT9/8n7/wgMRS9NObceP+gjRtChhCPX0vY5dQR90kVrrhfJiel68XgjhCRfxHEwe+iXhTBBiF8E8XRKK8P2tRtS/hHEDYOrQlMuvnyr+JfoIwUYnI/XfmLAgLrUtXozH6tNqsU/q0CIMRCZc7Vyhi3IEJ/aLUNvAg6grbJwJFdWrkRhDJhn4jHr7VoKBiN5UUQsVkwv6O36uQ96xXcdcvGIQ8VyK8Flo9ZPX/WVu+Xkl7jeSK5IJLXo3ufkhHkRmrkghVfG/CHPBx/lwH5AAAAskGaYC/AL8MQSJnOkv1chM0fxvxoER1raUYjFp6XkiRCwRE/f/7M4QGIpemg4smGMmfpfzCFgi9bQTesaCDuCb1aH71qN7W0CbvKv4MK4StYPfXp61aBEGKTLnyqlSGIlyBGrh9eNEIalQI+1Sw3gm69VSouGMErf6f9XozkM4IcFYxG8qH5Md8TX+r+Lr0P+i93x1yR/ozV6O8FV613rUNcnXF+idBFejtDb/gr9WIBVIAAAACfQZqAL8AvwxBImc6S/hM0fxvxoER1raUYoYZTUaP/+gvWte5OKWCP0R5C//6/hAYpemjfMfVTm4//kCfWvB5kyjiE5QVev4Jq0SKBI9HaCLVcsv9esUX6sQJy/icEmCe+BWvVoEQYiEy5YxbkCNfDXFQJefQhCYI1/D3oQ8FAQXyqn+PyY6uvV4NfV4a5II/XoQ9XLFLBtWi1A3iCYBK4AAAAhkGaoC/AKx6CmUEwxSZzpL9FYhM0fxvxoERVraUYiDLR6jR//0EzrWtYLL6L//r+EBiIXpoFDJmGImL9bQUei2h7qTZoEfCuT1frVod9em9en9fwhjcbi8Gq/gwxGBWvV4EQYpMuWMRLkBWY3BIv4EYYvlQ/Jg49FrL//D/q0BMeiPBHfAKlAAAAc0GawC/AKeMQw9Gl2kToKhikznSX6uQmaP4340CIq1tKMRBlo9BgX//X8IDFL00Tev4EfJl9FipVHa5VXBPrDvqwA2+tTetT1x2BQwIi/gIb1aBEGIhMuWMW5AycRA1XwJAQXyqn+PyYOb4JxClwBZVwCpwAAAB/QZrgL8Ap6W+C8YgkTOdJfwmaP4340CI61tKMRBlo9JzQWF//1/CAxS9NAoZM/r1XwTev4erragl9fTev4IfQlOgS+jdP6/gUl/AQ1atAiDFJlyxiJcgNBfwRiEJrBXghGIR5UPyYZEEw/Wi9l//h/1eAisI4L64dGIg/5oBN4AAAAJFBmwAvwC/DEEiZzpL+EzR/G/GgRHWtpRiIMtHo0QsEZf/9fwgMUvTQmMXVCFg7yYnjkWNYhYI/W0PerAE/o14KfRXh316NS8i5QKS/gIa9WgRBiky5YxEuQMuCHAj43BFXS/gkrgiGL5UPyYX+CEnra/ouHQRwTerwJHonVxcCLjcCAvtXiPgSPgSPgSPgSPj4AAAAbUGbIC/AL8MQSJnOkv4TNH8b8aBEda2lGIgy0eguvov/+v4QGKXpoSFErELB7kwX+v4ern9Xgg9fTetoED0WpvWp/WKHcO4NV/AZXonixi3IDOvgSAgvlVP8fkwcXr0EwhS5rV4EitegI0QsAmMAAACDQZtAL8ArwpYIBiCRM50l/CZo/jfjQIjrW0oxQwymijY/xx0EZ1QTF//1/CAxS9G4k3Hj/oL9a9yJ4iBGVwpqxBP62gl9c0EHo14JBCEwUeidAsr+AhvV4ET1uWMRLkBneLPqu00l/AjBBG8q/pj8mBfvV4Ei9F6AjzD/x+gQFapQCXwAAAB3QZtgL8AvwxBImc6S/hM0fxvxoER1raUYoYZTSjEZ2lHKz6CYv/+v4QGIpemgWRinv5BN6/gkGE8utWgROKgi9egX1/CIhYCTfEwQQTVrcsYiXIDQX8EXorwSBBE8q/pj8mGsJ4frgm9WgRV89+tfreAkRi+gEsgAAABwQZuAL8ArPcEoxBImc6S/hM0fxvxoER1raUYoYZTRPJBLfRf/9fwgMUvRuB/9bQSDCec/RngZvRagX1/AucMQI4hYJ71uWMRLkBoL+CLzCdVYhS0BCEEI8q/pj8mExCEz4Tw/fBRQFHAkXwJAhYBdIAAAAF5Bm6AvwC/DEEiZzpL+EzR/G/GgRHWtpRihhlNBgX//X8IDFL0bhQYrxoEnCeDpYQ8ZWiRQQ+vpvX8BPr+AyvXxYxbkB5bwSBBWuJ1T9NMfkwjh3AnerwEZ6veXALvAAAAAZ0GbwC/AL8MQSJnOkv4TGIrtKMUMMr0fwlDuSrVXRf/1fX6vCAxS9NCBn8IOP6CNpBiJal/Aiev4JfRfwSjiS50EHol4Eb0XoKsO4NV/AZXrcsYiXIDOvpfwQ+UTqpMGODDJg5rgCLIAAABjQZvgL8AvwxBImc6S/hMYiu0oxQwyvRYwl3gh9Xq+i//q3RKvCAxS9NCHq8CK+FNFPQVeiWhn1eM9agZvWoF9fwoIWAtq1uWMRLkBV4IcEq/gVcmDm+CT1jwJIhFgJMQTAJZAAAAAZUGaAC/AKp6CVTjlvBGMUmc6S/hMYiu0oxQwyvQYF//V+yVeEBil6aEjbj+/Ggj+QTXwS4bwRev4JBC6XqBm9egX1/AZV63LGIlyArMEOCRfwKuTCl5ROqmwR4frgcdngSBBMAucAAAAT0GaIC/AK0IWhyHFo0EQxEJnOkv4TGIrtKMUMMr0GBf/1b9WhAYpemhL0SoEF4V8FnotoJBC1hXAy+tQL6/gMoYpMuWMRLkBoL+BVyYAmWAAAABOQZpAL8AvwxBImc6S/hMYiu0oxQwyvR3HQRF//V4RGKXpo/kgcPX8EghYGf16CsQhcGi/g/9UhA+9KUo70M8WMW5AvcZAY+TAJjWrwCaQAAAAY0GaYC/AKz4gJarqoJRikznSX8JjEV2lGKGGV6cUiO/WoJi//o7QiMUvRub1yiBSwJYxG9jFPdyCX0W0EghYGf1qCrBLg1X8BSYZwTetyxiJcgNBfw5hnBzkwFSvuAiBCtAE0gAAAFpBmoAvwC/DEEiZzpL+ExiK7SjFDDK9GiEY1gjL//CIxHL003r0aMJd4EoQsEXr+Ai/XoF9fwGVWtyxiJcgQvRegbfV4IV/Xr+BR9erJhL1eIw7gIsYsqoBwIAAAABpQZqgL8AqYpYKxiCRM50l/CYxFdpRikr0xoxGPj6C9a1+UxuP/5An1rwSF//V4RGKXppvWo43Hjj8ge6wNfraCQQsCUIWHfWoJjo8Agd6EVYxbkDOIiYEj0ZoIV/Va/gU8mApfV5OWAbyAAAAb0GawC/AKsIJgoGIJEznSX8JjEV2lGKSvTGjEY+PoL1rX5WaL//0Eyr9YJy//wiMRC9NN69ApjF9+idBL6L+CQQsCF1BL69Avr+AyvX5YxEuQMuCHAlDkJnR0CFfwJQxGOQWIvJgKntFpUAkRCwCVwAAAHtBmuAvwC/DEEiZzpL+ExiK7SjFJXpjccRjEeQL9a+oKi//q0b69IMUvTTetZtx4/6CNo7jlaBDHEzJjFf0E3raCIQtCFgZ/WoF9fwGVWvyxiJcgNBf16PaCD1aCgYiHILEXkwLHorUIWI3RPwIg5bUMX1erwEaIR4BLoAAAABgQZsAL8AvwxBImc6S/i/ReiBiu0oxSV6DAv/6vG+tSDFL003r36vApDlfoJvX8EXFK1CFgZ/XoF9fwGV62LGIlyA0F/V6PaCCtWgoN+P/QXI+7u9iLyYGL1qBGGL6Ab2AAAAAcUGbIC/AL8MQSJnOkv4v0WogYrtKMUlegwL/+rRvr0gxS9NN61+rRV6vIIWBET8etQTetoIhC0IWBn9ah7Duc6E2IJgsW4lxa/gIqgiSBA9CusYtyA0r0W0EF6tYhfAo4JBiI7EXkwLwxeaBKGL6Ab2AAAAAYUGbQC/AL8MQSJnOkv4v0XogYrtKMUleihCwTF//V431qQYpemm9e/V4r1aBu9fwRCFoQuOUuZQJIhYd9egX1/ARa6B7hYQiwWDEIuQGgv4EoQri8mBfWBx98TAjCEeAb2AAAABaQZtgL8Aq/iybvu4JxiHEznSX8X6LUQMV2lGKSvT7cFJf/1aN9ekGKXppvWv1aB49bQRCFoQuOXlAkiFh31qBfX8BmjES5AwvBL4G9fwJXIrxeTC6+0diAJOgAAAAUkGbgC/AL8MQSJnOkv4v0XogYrtKMUlegwL/+rxvrUgxS9NN69+rwKgwkuGSCT1/BFxStQhYEgQQtL4qHfROgX1/AZoxEuQGgv4FXJhbB7gCT4AAAABZQZugL8AvwxBImc6S/i/RaiBiu0oxSV6DAv/6tG+vSDFL003rX6tA8etoIhC0IWBn9agX1/Bn6ugJoYiXIDQX8Crkwx4IheqmSBJEL4CRwI+AjcCMKQpQC7QAAABbQZvAL8AvwxBImc6S/i/ReiBiu0oxSV6DAv/6vG+tSDFL003r36vA8ev4IhC0IWt1zwMvr0C+v44QsEvqyBxwQ4KRiJcgNBfwUegg6C3JgXvQVeBI9XgSueAXWAAAAFlBm+AvwCuDkOpECIYiEznSX8X6LUQMV2lGKSvQYF//Vo316QYpemm9a/Vov1YgbfW0EQhaELXrGgZfWoF9fwZ+roCaGIlyA0F/BOKRYLsmBYGLaBO9WgG/gAAAAFxBmgAvwC/DEEiZzpL+L9F6IGK7SjFJXoMC//q8b61IMUvTTevfq8V6/gbvX8EXFIjUIWvR8oEf1ZB3ghwOvqyBT9WgRxiNcgNBfwReivBnkwv6vAgjFtAnerwDfwAAAFNBmiAvwC/DEFCZzpL+L9HqIGK7SjFJXoMC//q0b69IMUvTTetfq0VWv4G71tD6+leUQtN/XyBl9egJL1eBTrVoEcYiXIDQX8CrkwFN6O0CDyQC/QAAAHhBmkAvwC/DEFCZzpL+L9H6IGK7SjFJXoMC//q8b61IMUvTTevfq8huP/HQX617TetoG71/BF6v4FHiFq9c8CJgScEPrUE/yCEeBE+sDioIfRGgl+C69Whr4LRiNchv4Ej6wJHGRdMgNS/gVcmApsCTgSMCT+WAXaAAAABWQZpgL8AvwxBQmc6S/i/R6iBiu0oxSV6DAv/6tG+vSDFL003rX6tFev4G71tBIIXHLygZvXoCS9XgU/V4EcYiXIDQX9ei/gU8lagWBi2gTxCwNfq8AqcAAABWQZqAL8AvwxBQmc6S/hMYju0oxSV6DAv/6vG+tSDFL003r36vFetoEQQihB6wFXo34f9FaUQuOXlAfHq0Cn6tAjjEa5AaXotoFOiVqBYGLaAuvVoBU4AAAAA/QZqgL8AvwxBQmc6S/hMYiu0oxUfQYF//VoRGKXpoR9XgbvW0Pl//lELBP62gNL1eBT9XgRxi3IBJbJRagCZYAAAAOUGawC/AL8MQUJnOkv4TGIrtKMVH0GBf/1eERil6aB/9fw/fKIXHLygGSGLcgElsmBYGLaA4BCwCWwAAAGVBmuAvwC/DEFCZzpL+ExiK7SjFR9BgX/9WhEYpemhXjl98OQI/EwRetoJBC45eWMRS40B7+rQKfq0COMRrkBWYIcE3ov4IcEuDLJXoW+BCGLab0RoEjeBI7k7gRBii7ydovQCVwAAAAFFBmwAvwC/DEFCZzpL+ExiK7SjFR9GDFYNiCQv/6vCIxS9NCghFRga/Rvwz6O0WIXHLyxBJcAKVWrQI4xGuQGl6LaBTyVqBYGLaatEaBI5IBv4AAABiQZsgL8ArQhBJQSDFJnOkv4YGKj6UYS5tBWX/9WjfRekGKXppvWv1aU3whF/oPdYE/1/B7WrRYhccvLGKXGgLv16Dz1eBTvVoEcYiXIDS9F/Ap0StQLAxbQEoOW0E3q8AqcAAAABLQZtAL8AvwxBYmc6CoxHdpRio+gwL/+rwiMUvTQLfraCT1tDJf/4sQuOXlr6V4C79FqAj/RHgRxiJcgNL0W0CmX/+BYGLab1eAIHgAAAAQ0GbYC/AK6KWCEYgsTOdBoYio+lEK4Ky//q0IjFL2gWHwp3ev4JPX8EghcUsBeei9AawxGuQCS5KP0CwMW0BderQCpwAAAA5QZuAL8AvwxBYmc6DQxFR9BgX/9XhEYpe0C361AkCFgL30WoDWGI1yASXJR6gWBi2iPVKgFl6vAKnAAAAP0GboC/AL8MQYSToNDEdH0GBf/1aERil7QqMIUtOgj9Xi/V4FX1eLELAXvr0BrDEa5AJLRKPUCwMW0BderQCpwAAADhBm8AvwC/DEGEk6DQxF9GiFcEZf/4RwQ4VGI5adBd6tAwCFxSwF561AawxGuQCS+i9AsDFtAEGwAAAACZBm+AvwC/DEGkk6DQhFgVhCKWgLvRXgYBC4pYC89egNYYhFyAOKgAAABpBmgArwC/DEGkk6DQhFgOQQi4pYBkhCwBxUAAAABxBmiAnwC/CFhoQsBOCFgSBC4hYBkhCwBH/JAKXAAAHs21vb3YAAABsbXZoZAAAAAAAAAAAAAAAAAAAA+gAACcQAAEAAAEAAAAAAAAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIAAAbddHJhawAAAFx0a2hkAAAAAwAAAAAAAAAAAAAAAQAAAAAAACcQAAAAAAAAAAAAAAAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAQAAAAASAAAABsAAAAAAAJGVkdHMAAAAcZWxzdAAAAAAAAAABAAAnEAAAAAAAAQAAAAAGVW1kaWEAAAAgbWRoZAAAAAAAAAAAAAAAAAAAPAAAAlgAVcQAAAAAAC1oZGxyAAAAAAAAAAB2aWRlAAAAAAAAAAAAAAAAVmlkZW9IYW5kbGVyAAAABgBtaW5mAAAAFHZtaGQAAAABAAAAAAAAAAAAAAAkZGluZgAAABxkcmVmAAAAAAAAAAEAAAAMdXJsIAAAAAEAAAXAc3RibAAAAJRzdHNkAAAAAAAAAAEAAACEYXZjMQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAASAAbAASAAAAEgAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABj//wAAAC5hdmNDAULAHv/hABZnQsAe2QBIDehAAAADAEAAAA8DxYuSAQAFaMuDyyAAAAAYc3R0cwAAAAAAAAABAAABLAAAAgAAAAAYc3RzcwAAAAAAAAACAAAAAQAAAPsAAAAcc3RzYwAAAAAAAAABAAAAAQAAASwAAAABAAAExHN0c3oAAAAAAAAAAAAAASwAABW5AAAB2QAAAd0AAAHiAAAByQAAAfoAAAGhAAABvgAAAY8AAAGnAAABvQAAAZwAAAGvAAABaQAAAZwAAAGPAAABjwAAAXAAAAGyAAABgQAAAWwAAAF1AAABqgAAAXgAAAGGAAABfwAAAaMAAAGQAAABnwAAAX4AAAGYAAABmwAAAZ8AAAGzAAABvwAAAbkAAAGfAAABlQAAAdMAAAHAAAABmwAAAXEAAAG1AAABuQAAAcgAAAGnAAACGwAAAesAAAH0AAABwAAAAbwAAAHAAAAB0QAAAigAAAHRAAABzAAAAawAAAHjAAAB0QAAAdMAAAHuAAACJQAAAasAAAHfAAAByAAAAZcAAAGlAAAB6AAAAdQAAAHUAAABywAAAgsAAAF9AAABvAAAAakAAAHHAAABgwAAAcUAAAG8AAAB9gAAAZUAAAHIAAABrwAAAf0AAAGtAAAB7wAAAbEAAAHtAAAByAAAAY4AAAGNAAABsgAAAaEAAAGZAAACIwAAAe8AAAIqAAAB9AAAAcsAAAH0AAAB8gAAAh4AAAIwAAACCQAAAeQAAAIKAAACEQAAAk8AAAIHAAAB4gAAAcIAAAIaAAAB+QAAAdgAAAH/AAACKgAAAbUAAAH3AAAB1QAAAfsAAAIFAAABtgAAAfkAAAIlAAACCgAAAdUAAAHXAAAB9gAAAewAAAGdAAABugAAAd4AAAHEAAACEQAAAfMAAAHmAAABugAAAZ8AAAG5AAABwAAAAbAAAAHqAAABugAAAdMAAAGjAAABmQAAAZ0AAAGnAAABxgAAAaAAAAHBAAABtgAAAc4AAAGiAAABjQAAAZUAAAGqAAABmwAAAXIAAAGkAAABmAAAAYsAAAFrAAABmgAAAccAAAF+AAABpwAAAZIAAAGLAAABwQAAAVEAAAGtAAABjwAAAXkAAAG+AAABhwAAAXgAAAGIAAABqQAAAV0AAAGDAAABnAAAAZYAAAGSAAABjQAAAXYAAAGDAAABSQAAAVIAAAFiAAABKgAAAW4AAAFiAAABJQAAAU8AAA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type=\"video/mp4\">\n",
" Your browser does not support the video tag.\n",
"</video>"
],
@@ -203,7 +203,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.8"
+ "version": "3.7.7"
}
},
"nbformat": 4,
diff --git a/pystencils/backends/dot.py b/pystencils/backends/dot.py
index 83ae1c705..61a9e30a4 100644
--- a/pystencils/backends/dot.py
+++ b/pystencils/backends/dot.py
@@ -50,7 +50,7 @@ class DotPrinter(Printer):
def __shortened(node):
- from pystencils.astnodes import LoopOverCoordinate, KernelFunction, SympyAssignment, Block, Conditional
+ from pystencils.astnodes import LoopOverCoordinate, KernelFunction, SympyAssignment, Conditional
if isinstance(node, LoopOverCoordinate):
return "Loop over dim %d" % (node.coordinate_to_loop_over,)
elif isinstance(node, KernelFunction):
@@ -60,8 +60,6 @@ def __shortened(node):
return f"Func: {node.function_name} ({','.join(param_names)})"
elif isinstance(node, SympyAssignment):
return repr(node.lhs)
- elif isinstance(node, Block):
- return "Block" + str(id(node))
elif isinstance(node, Conditional):
return repr(node)
else:
diff --git a/pystencils/cpu/kernelcreation.py b/pystencils/cpu/kernelcreation.py
index 457944db6..81daf49fc 100644
--- a/pystencils/cpu/kernelcreation.py
+++ b/pystencils/cpu/kernelcreation.py
@@ -189,10 +189,6 @@ def add_openmp(ast_node, schedule="static", num_threads=True, collapse=None, ass
except TypeError:
loop_range = None
- if num_threads is None:
- import multiprocessing
- num_threads = multiprocessing.cpu_count()
-
if loop_range is not None and loop_range < num_threads and not collapse:
contained_loops = [l for l in loop_to_parallelize.body.args if isinstance(l, LoopOverCoordinate)]
if len(contained_loops) == 1:
diff --git a/pystencils/datahandling/parallel_datahandling.py b/pystencils/datahandling/parallel_datahandling.py
index 82d5b4cb6..9c1462407 100644
--- a/pystencils/datahandling/parallel_datahandling.py
+++ b/pystencils/datahandling/parallel_datahandling.py
@@ -301,7 +301,7 @@ class ParallelDataHandling(DataHandling):
create_scheme = wlb.createUniformBufferedScheme if buffered else wlb.createUniformDirectScheme
if target == 'cpu':
create_packing = wlb.field.createPackInfo if buffered else wlb.field.createMPIDatatypeInfo
- if not buffered and stencil_restricted:
+ if buffered and stencil_restricted:
create_packing = wlb.field.createStencilRestrictedPackInfo
else:
assert target == 'gpu'
diff --git a/pystencils/fd/spatial.py b/pystencils/fd/spatial.py
index fda6773ce..2355906a8 100644
--- a/pystencils/fd/spatial.py
+++ b/pystencils/fd/spatial.py
@@ -72,43 +72,12 @@ def fd_stencils_forth_order_isotropic(indices, dx, fa):
return stencils[dim].apply(fa) / dx
-def fd_stencils_isotropic_high_density_code(indices, dx, fa):
- dim = fa.field.spatial_dimensions
- if dim == 1:
- return fd_stencils_standard(indices, dx, fa)
- elif dim == 2:
- order = len(indices)
-
- if order == 1:
- idx = indices[0]
- assert 0 <= idx < 2
- other_idx = 1 if indices[0] == 0 else 0
- weights = {-1: sp.Rational(1, 12) / dx,
- 0: sp.Rational(1, 3) / dx,
- 1: sp.Rational(1, 12) / dx}
- upper_terms = sum(fa.neighbor(idx, +1).neighbor(other_idx, off) * w for off, w in weights.items())
- lower_terms = sum(fa.neighbor(idx, -1).neighbor(other_idx, off) * w for off, w in weights.items())
- return upper_terms - lower_terms
- elif order == 2:
- if indices[0] == indices[1]:
- idx = indices[0]
- diagonals = sp.Rational(1, 8) * sum(fa.neighbor(0, i).neighbor(1, j) for i in (-1, 1) for j in (-1, 1))
- div_direction = sp.Rational(1, 2) * sum(fa.neighbor(idx, i) for i in (-1, 1))
- center = - sp.Rational(3, 2) * fa
- return (diagonals + div_direction + center) / (dx ** 2)
- else:
- return fd_stencils_standard(indices, dx, fa)
- raise NotImplementedError("Supports only derivatives up to order 2 for 1D and 2D setups")
-
-
def discretize_spatial(expr, dx, stencil=fd_stencils_standard):
if isinstance(stencil, str):
if stencil == 'standard':
stencil = fd_stencils_standard
elif stencil == 'isotropic':
stencil = fd_stencils_isotropic
- elif stencil == 'isotropic_hd':
- stencil = fd_stencils_isotropic_high_density_code
else:
raise ValueError("Unknown stencil. Supported 'standard' and 'isotropic'")
@@ -167,8 +136,6 @@ def discretize_spatial_staggered(expr, dx, stencil=fd_stencils_standard):
# -------------------------------------- special stencils --------------------------------------------------------------
-
-
@memorycache(maxsize=1)
def forth_order_2d_derivation() -> Tuple[FiniteDifferenceStencilDerivation.Result, ...]:
# Symmetry, isotropy and 4th order conditions are not enough to fully specify the stencil
diff --git a/pystencils/field.py b/pystencils/field.py
index bdff32343..78c420c8c 100644
--- a/pystencils/field.py
+++ b/pystencils/field.py
@@ -510,8 +510,6 @@ class Field(AbstractField):
if type(offset) is str:
offset = tuple(direction_string_to_offset(offset, self.spatial_dimensions))
offset = tuple([o * sp.Rational(1, 2) for o in offset])
- if type(offset) is not tuple:
- offset = (offset,)
if len(offset) != self.spatial_dimensions:
raise ValueError("Wrong number of spatial indices: "
"Got %d, expected %d" % (len(offset), self.spatial_dimensions))
@@ -624,15 +622,15 @@ class Field(AbstractField):
return self.coordinate_transform @ \
(self.coordinate_origin + pystencils.x_staggered_vector(self.spatial_dimensions))
- def index_to_physical(self, index_coordinates, staggered=False):
+ def index_to_physical(self, index_coordinates: sp.Matrix, staggered=False):
if staggered:
- index_coordinates = sp.Matrix([i + 0.5 for i in index_coordinates])
+ index_coordinates = sp.Matrix([0.5] * len(self.coordinate_origin)) + index_coordinates
if hasattr(self.coordinate_transform, '__call__'):
return self.coordinate_transform(self.coordinate_origin + index_coordinates)
else:
return self.coordinate_transform @ (self.coordinate_origin + index_coordinates)
- def physical_to_index(self, physical_coordinates, staggered=False):
+ def physical_to_index(self, physical_coordinates: sp.Matrix, staggered=False):
if hasattr(self.coordinate_transform, '__call__'):
if hasattr(self.coordinate_transform, 'inv'):
return self.coordinate_transform.inv()(physical_coordinates) - self.coordinate_origin
@@ -649,10 +647,6 @@ class Field(AbstractField):
return rtn
- def index_to_staggered_physical_coordinates(self, symbol_vector):
- symbol_vector += sp.Matrix([0.5] * self.spatial_dimensions)
- return self.create_physical_coordinates(symbol_vector)
-
def set_coordinate_origin_to_field_center(self):
self.coordinate_origin = -sp.Matrix([i / 2 for i in self.spatial_shape])
diff --git a/pystencils/kerncraft_coupling/kerncraft_interface.py b/pystencils/kerncraft_coupling/kerncraft_interface.py
index c0dc5888f..1beb58059 100644
--- a/pystencils/kerncraft_coupling/kerncraft_interface.py
+++ b/pystencils/kerncraft_coupling/kerncraft_interface.py
@@ -118,12 +118,6 @@ class PyStencilsKerncraftKernel(KernelCode):
permuted_coord = [sp.sympify(coord[i]) for i in layout]
target_dict[fa.field.name].append(permuted_coord)
- # Scalars may be safely ignored
- # for param in self.kernel_ast.get_parameters():
- # if not param.is_field_parameter:
- # # self.set_variable(param.symbol.name, str(param.symbol.dtype), None)
- # self.sources[param.symbol.name] = [None]
-
# data type
self.datatype = list(self.variables.values())[0][0]
diff --git a/pystencils/stencil.py b/pystencils/stencil.py
index 28d179c50..668ea96bf 100644
--- a/pystencils/stencil.py
+++ b/pystencils/stencil.py
@@ -319,6 +319,7 @@ def plot_2d(stencil, axes=None, figure=None, data=None, textsize='12', **kwargs)
Args:
stencil: sequence of directions
axes: optional matplotlib axes
+ figure: optional matplotlib figure
data: data to annotate the directions with, if none given, the indices are used
textsize: size of annotation text
"""
@@ -374,6 +375,7 @@ def plot_3d_slicing(stencil, slice_axis=2, figure=None, data=None, **kwargs):
Args:
stencil: stencil as sequence of directions
slice_axis: 0, 1, or 2 indicating the axis to slice through
+ figure: optional matplotlib figure
data: optional data to print as text besides the arrows
"""
import matplotlib.pyplot as plt
@@ -468,8 +470,8 @@ def plot_3d(stencil, figure=None, axes=None, data=None, textsize='8'):
else:
annotation = str(annotation)
- axes.text(d[0] * text_offset, d[1] * text_offset, d[2] * text_offset,
- annotation, verticalalignment='center', zorder=30,
+ axes.text(x=d[0] * text_offset, y=d[1] * text_offset, z=d[2] * text_offset,
+ s=annotation, verticalalignment='center', zorder=30,
size=textsize, bbox=dict(boxstyle=text_box_style, facecolor='#777777', alpha=0.6, linewidth=0))
axes.set_xlim([-text_offset * 1.1, text_offset * 1.1])
diff --git a/pystencils/transformations.py b/pystencils/transformations.py
index 100d0c20a..6fd80687b 100644
--- a/pystencils/transformations.py
+++ b/pystencils/transformations.py
@@ -850,6 +850,15 @@ class KernelConstraintsCheck:
elif type_constants and isinstance(rhs, sp.Number):
return cast_func(rhs, create_type(self._type_for_symbol['_constant']))
# Very important that this clause comes before BooleanFunction
+ elif isinstance(rhs, sp.Equality):
+ if isinstance(rhs.args[1], sp.Number):
+ return sp.Equality(
+ self.process_expression(rhs.args[0], type_constants),
+ rhs.args[1])
+ else:
+ return sp.Equality(
+ self.process_expression(rhs.args[0], type_constants),
+ self.process_expression(rhs.args[1], type_constants))
elif isinstance(rhs, cast_func):
return cast_func(
self.process_expression(rhs.args[0], type_constants=False),
diff --git a/pystencils_tests/test_address_of.py b/pystencils_tests/test_address_of.py
index 717f6e437..659f5d92f 100644
--- a/pystencils_tests/test_address_of.py
+++ b/pystencils_tests/test_address_of.py
@@ -1,7 +1,7 @@
"""
Test of pystencils.data_types.address_of
"""
-
+import sympy as sp
import pystencils
from pystencils.data_types import PointerType, address_of, cast_func, create_type
from pystencils.simp.simplifications import sympy_cse
@@ -11,6 +11,10 @@ def test_address_of():
x, y = pystencils.fields('x,y: int64[2d]')
s = pystencils.TypedSymbol('s', PointerType(create_type('int64')))
+ assert address_of(x[0, 0]).canonical() == x[0, 0]
+ assert address_of(x[0, 0]).dtype == PointerType(x[0, 0].dtype, restrict=True)
+ assert address_of(sp.Symbol("a")).dtype == PointerType('void', restrict=True)
+
assignments = pystencils.AssignmentCollection({
s: address_of(x[0, 0]),
y[0, 0]: cast_func(s, create_type('int64'))
diff --git a/pystencils_tests/test_aligned_array.py b/pystencils_tests/test_aligned_array.py
index f22c7682f..9635492eb 100644
--- a/pystencils_tests/test_aligned_array.py
+++ b/pystencils_tests/test_aligned_array.py
@@ -12,7 +12,7 @@ def is_aligned(arr, alignment, byte_offset=0):
def test_1d_arrays():
- for alignment in [8, 8*4]:
+ for alignment in [8, 8*4, True]:
for shape in [17, 16, (16, 16), (17, 17), (18, 18), (19, 19)]:
arrays = [
aligned_zeros(shape, alignment),
@@ -25,7 +25,7 @@ def test_1d_arrays():
def test_3d_arrays():
for order in ('C', 'F'):
- for alignment in [8, 8*4]:
+ for alignment in [8, 8*4, True]:
for shape in [(16, 16), (17, 17), (18, 18), (19, 19)]:
arrays = [
aligned_zeros(shape, alignment, order=order),
diff --git a/pystencils_tests/test_basic_usage_llvm.ipynb b/pystencils_tests/test_basic_usage_llvm.ipynb
index 4976b4b08..4b7f84341 100644
--- a/pystencils_tests/test_basic_usage_llvm.ipynb
+++ b/pystencils_tests/test_basic_usage_llvm.ipynb
@@ -62,11 +62,14 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": 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+ "text/latex": [
+ "$\\displaystyle {{dst}_{(0,0)}} \\leftarrow {{src}_{(0,0)}} \\left(1.0 - \\omega\\right) + \\frac{\\omega \\left({{src}_{(1,0)}} + {{src}_{(0,1)}} + {{src}_{(0,-1)}} + {{src}_{(-1,0)}}\\right)}{4}$"
+ ],
"text/plain": [
- " ω⋅(src_E + src_N + src_S + src_W)\n",
- "dst_C := src_C⋅(-ω + 1.0) + ─────────────────────────────────\n",
- " 4 "
+ " ω⋅(src_E + src_N + src_S + src_W)\n",
+ "dst_C := src_C⋅(1.0 - ω) + ─────────────────────────────────\n",
+ " 4 "
]
},
"execution_count": 3,
@@ -99,14 +102,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "KernelFunction kernel([<double * RESTRICT fd_dst>, <double * RESTRICT const fd_src>, <double omega>])\n",
+ "KernelFunction kernel([_data_dst, _data_src, omega])\n",
"\tBlock for(ctr_0=1; ctr_0<29; ctr_0+=1)\n",
- "\t\tBlock fd_dst_C ↠pointer_arithmetic_func(fd_dst, 20*ctr_0)\n",
- "\t\tfd_src_C ↠pointer_arithmetic_func(fd_src, 20*ctr_0)\n",
- "\t\tfd_src_E ↠pointer_arithmetic_func(fd_src, 20*ctr_0 + 20)\n",
- "\t\tfd_src_W ↠pointer_arithmetic_func(fd_src, 20*ctr_0 - 20)\n",
+ "\t\tBlock _data_dst_00 ↠pointer_arithmetic_func(_data_dst, 20*ctr_0)\n",
+ "\t\t_data_src_00 ↠pointer_arithmetic_func(_data_src, 20*ctr_0)\n",
+ "\t\t_data_src_01 ↠pointer_arithmetic_func(_data_src, 20*ctr_0 + 20)\n",
+ "\t\t_data_src_0m1 ↠pointer_arithmetic_func(_data_src, 20*ctr_0 - 20)\n",
"\t\tfor(ctr_1=1; ctr_1<19; ctr_1+=1)\n",
- "\t\t\tBlock fd_dst_C[ctr_1] ↠omega*(fd_src_C[ctr_1 + 1] + fd_src_C[ctr_1 - 1] + fd_src_E[ctr_1] + fd_src_W[ctr_1])/4 + (omega*cast_func(-1, double) + 1.0)*fd_src_C[ctr_1]\n",
+ "\t\t\tBlock _data_dst_00[ctr_1] ↠omega*(_data_src_00[ctr_1 + 1] + _data_src_00[ctr_1 - 1] + _data_src_01[ctr_1] + _data_src_0m1[ctr_1])*cast_func(1/4, double) + (omega*cast_func(-1, double) + cast_func(1.0, double))*_data_src_00[ctr_1]\n",
"\t\t\n",
"\t\n",
"\n"
@@ -138,124 +141,145 @@
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" \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
- "<!-- Generated by graphviz version 2.38.0 (20140413.2041)\n",
+ "<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n",
" -->\n",
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- " viewBox=\"0.00 0.00 569.74 476.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
+ "<svg width=\"864pt\" height=\"476pt\"\n",
+ " viewBox=\"0.00 0.00 864.48 476.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
"<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 472)\">\n",
"<title>%3</title>\n",
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- "<text text-anchor=\"middle\" x=\"249.896\" y=\"-446.3\" font-family=\"Times,serif\" font-size=\"14.00\">Func: kernel (dst,src,omega)</text>\n",
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@@ -348,11 +372,14 @@
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{
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+ "image/png": "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\n",
"text/plain": [
- "<Figure size 640x480 with 1 Axes>"
+ "<Figure size 432x288 with 1 Axes>"
]
},
- "metadata": {},
+ "metadata": {
+ "needs_background": "light"
+ },
"output_type": "display_data"
}
],
@@ -390,7 +417,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.5"
+ "version": "3.7.7"
}
},
"nbformat": 4,
diff --git a/pystencils_tests/test_blocking.py b/pystencils_tests/test_blocking.py
index 1c5646271..3d6436a74 100644
--- a/pystencils_tests/test_blocking.py
+++ b/pystencils_tests/test_blocking.py
@@ -22,16 +22,21 @@ def check_equivalence(assignments, src_arr):
cpu_vectorize_info=vectorization).compile()
without_blocking = ps.create_kernel(assignments).compile()
+ only_omp = ps.create_kernel(assignments, cpu_openmp=2).compile()
+
print(f" openmp {openmp}, vectorization {vectorization}")
dst_arr = np.zeros_like(src_arr)
dst2_arr = np.zeros_like(src_arr)
+ dst3_arr = np.zeros_like(src_arr)
ref_arr = np.zeros_like(src_arr)
np.copyto(src_arr, np.random.rand(*src_arr.shape))
with_blocking(src=src_arr, dst=dst_arr)
with_blocking_only_over_y(src=src_arr, dst=dst2_arr)
without_blocking(src=src_arr, dst=ref_arr)
+ only_omp(src=src_arr, dst=dst3_arr)
np.testing.assert_almost_equal(ref_arr, dst_arr)
np.testing.assert_almost_equal(ref_arr, dst2_arr)
+ np.testing.assert_almost_equal(ref_arr, dst3_arr)
def test_jacobi3d_var_size():
@@ -65,3 +70,11 @@ def test_jacobi3d_fixed_size():
arr = np.empty([8*4, 16*2, 4*3])
src, dst = ps.fields("src, dst: double[3D]", src=arr, dst=arr)
check_equivalence(jacobi(dst, src), arr)
+
+
+def test_jacobi3d_fixed_field_size():
+ src, dst = ps.fields("src, dst: double[3, 5, 6]", layout='c')
+
+ print("Fixed Field Size: Smaller than block sizes")
+ arr = np.empty([3, 5, 6])
+ check_equivalence(jacobi(dst, src), arr)
\ No newline at end of file
diff --git a/pystencils_tests/test_boundary.py b/pystencils_tests/test_boundary.py
index 421cc2565..b5c0f9f97 100644
--- a/pystencils_tests/test_boundary.py
+++ b/pystencils_tests/test_boundary.py
@@ -8,6 +8,7 @@ from pystencils import Assignment, create_kernel
from pystencils.boundaries import BoundaryHandling, Dirichlet, Neumann, add_neumann_boundary
from pystencils.datahandling import SerialDataHandling
from pystencils.slicing import slice_from_direction
+from pystencils.timeloop import TimeLoop
def test_kernel_vs_copy_boundary():
@@ -88,6 +89,136 @@ def test_kernel_vs_copy_boundary():
boundary_handling.geometry_to_vtk(file_name=os.path.join(tmp_dir, 'test_output1'), ghost_layers=False)
boundary_handling.geometry_to_vtk(file_name=os.path.join(tmp_dir, 'test_output2'), ghost_layers=True)
+ boundaries = list(boundary_handling._boundary_object_to_boundary_info.keys()) + ['domain']
+ boundary_handling.geometry_to_vtk(file_name=os.path.join(tmp_dir, 'test_output3'),
+ boundaries=boundaries[0], ghost_layers=False)
+
+
+def test_boundary_gpu():
+ pytest.importorskip('pycuda')
+ dh = SerialDataHandling(domain_size=(7, 7), default_target="gpu")
+ src = dh.add_array('src')
+ dh.fill("src", 0.0, ghost_layers=True)
+ dh.fill("src", 1.0, ghost_layers=False)
+ src_cpu = dh.add_array('src_cpu', gpu=False)
+ dh.fill("src_cpu", 0.0, ghost_layers=True)
+ dh.fill("src_cpu", 1.0, ghost_layers=False)
+
+ boundary_stencil = [(1, 0), (-1, 0), (0, 1), (0, -1)]
+ boundary_handling_cpu = BoundaryHandling(dh, src_cpu.name, boundary_stencil,
+ name="boundary_handling_cpu", target='cpu')
+
+ boundary_handling = BoundaryHandling(dh, src.name, boundary_stencil,
+ name="boundary_handling_gpu", target='gpu')
+
+ neumann = Neumann()
+ for d in ('N', 'S', 'W', 'E'):
+ boundary_handling.set_boundary(neumann, slice_from_direction(d, dim=2))
+ boundary_handling_cpu.set_boundary(neumann, slice_from_direction(d, dim=2))
+
+ boundary_handling.prepare()
+ boundary_handling_cpu.prepare()
+
+ boundary_handling_cpu()
+
+ dh.all_to_gpu()
+ boundary_handling()
+ dh.all_to_cpu()
+ np.testing.assert_almost_equal(dh.cpu_arrays["src_cpu"], dh.cpu_arrays["src"])
+
+
+def test_boundary_utility():
+ dh = SerialDataHandling(domain_size=(7, 7))
+ src = dh.add_array('src')
+ dh.fill("src", 0.0, ghost_layers=True)
+
+ boundary_stencil = [(1, 0), (-1, 0), (0, 1), (0, -1)]
+
+ boundary_handling = BoundaryHandling(dh, src.name, boundary_stencil,
+ name="boundary_handling", target='cpu')
+
+ neumann = Neumann()
+ dirichlet = Dirichlet(2)
+ for d in ('N', 'S', 'W', 'E'):
+ boundary_handling.set_boundary(neumann, slice_from_direction(d, dim=2))
+
+ boundary_handling.set_boundary(neumann, (slice(2, 4, None), slice(2, 4, None)))
+
+ boundary_handling.prepare()
+
+ assert boundary_handling.get_flag(boundary_handling.boundary_objects[0]) == 2
+ assert boundary_handling.shape == dh.shape
+ assert boundary_handling.flag_array_name == 'boundary_handlingFlags'
+ mask_neumann = boundary_handling.get_mask((slice(0, 7), slice(0, 7)), boundary_handling.boundary_objects[0])
+ np.testing.assert_almost_equal(mask_neumann[1:3, 1:3], 2)
+
+ mask_domain = boundary_handling.get_mask((slice(0, 7), slice(0, 7)), "domain")
+ assert np.sum(mask_domain) == 7 ** 2 - 4
+
+ def set_sphere(x, y):
+ mid = (4, 4)
+ radius = 2
+ return (x - mid[0]) ** 2 + (y - mid[1]) ** 2 < radius ** 2
+
+ boundary_handling.set_boundary(dirichlet, mask_callback=set_sphere, force_flag_value=4)
+ mask_dirichlet = boundary_handling.get_mask((slice(0, 7), slice(0, 7)), boundary_handling.boundary_objects[1])
+ assert np.sum(mask_dirichlet) == 48
+
+ assert boundary_handling.set_boundary("domain") == 1
+
+ assert boundary_handling.set_boundary(dirichlet, mask_callback=set_sphere, force_flag_value=8, replace=False) == 4
+ assert boundary_handling.set_boundary(dirichlet, force_flag_value=16, replace=False) == 4
+
+ assert boundary_handling.set_boundary_where_flag_is_set(boundary_handling.boundary_objects[0], 16) == 16
+
+
+def test_add_fix_steps():
+ dh = SerialDataHandling(domain_size=(7, 7))
+ src = dh.add_array('src')
+ dh.fill("src", 0.0, ghost_layers=True)
+ dh.fill("src", 1.0, ghost_layers=False)
+ boundary_stencil = [(1, 0), (-1, 0), (0, 1), (0, -1)]
+
+ boundary_handling = BoundaryHandling(dh, src.name, boundary_stencil,
+ name="boundary_handling", target='cpu')
+
+ neumann = Neumann()
+ for d in ('N', 'S', 'W', 'E'):
+ boundary_handling.set_boundary(neumann, slice_from_direction(d, dim=2))
+
+ timeloop = TimeLoop(steps=1)
+ boundary_handling.add_fixed_steps(timeloop)
+
+ timeloop.run()
+ assert np.sum(dh.cpu_arrays['src']) == 7 * 7 + 7 * 4
+
+
+def test_boundary_data_setter():
+ dh = SerialDataHandling(domain_size=(7, 7))
+ src = dh.add_array('src')
+ dh.fill("src", 0.0, ghost_layers=True)
+ dh.fill("src", 1.0, ghost_layers=False)
+ boundary_stencil = [(1, 0), (-1, 0), (0, 1), (0, -1)]
+
+ boundary_handling = BoundaryHandling(dh, src.name, boundary_stencil,
+ name="boundary_handling", target='cpu')
+
+ neumann = Neumann()
+ for d in 'N':
+ boundary_handling.set_boundary(neumann, slice_from_direction(d, dim=2))
+
+ boundary_handling.prepare()
+
+ for b in dh.iterate(ghost_layers=True):
+ index_array_bd = b[boundary_handling._index_array_name]
+ data_setter = index_array_bd.boundary_object_to_data_setter[boundary_handling.boundary_objects[0]]
+
+ y_pos = data_setter.boundary_cell_positions(1)
+
+ assert all(y_pos == 5.5)
+ assert np.all(data_setter.link_offsets() == [0, -1])
+ assert np.all(data_setter.link_positions(1) == 6.)
+
@pytest.mark.parametrize('with_indices', ('with_indices', False))
def test_dirichlet(with_indices):
diff --git a/pystencils_tests/test_cudagpu.py b/pystencils_tests/test_cudagpu.py
index f5efd517f..520d859bf 100644
--- a/pystencils_tests/test_cudagpu.py
+++ b/pystencils_tests/test_cudagpu.py
@@ -157,3 +157,9 @@ def test_block_indexing():
bi = BlockIndexing(f, make_slice[:, :, :], block_size=(32, 1, 1), permute_block_size_dependent_on_layout=False)
assert bi.call_parameters((1, 16, 16))['block'] == (1, 16, 2)
+
+ bi = BlockIndexing(f, make_slice[:, :, :], block_size=(16, 8, 2), maximum_block_size="auto")
+ # This function should be used if number of needed registers is known. Can be determined with func.num_regs
+ blocks = bi.limit_block_size_by_register_restriction([1024, 1024, 1], 1000)
+
+ assert sum(blocks) < sum([1024, 1024, 1])
diff --git a/pystencils_tests/test_data/datahandling_parallel_load_test/dst.dat b/pystencils_tests/test_data/datahandling_parallel_load_test/dst.dat
new file mode 100644
index 0000000000000000000000000000000000000000..204552486f77c485a4dd333a10eff82f9d44aa9f
GIT binary patch
literal 304
YcmWe&fB*$XC<9D=u!rzQY4mUa0M%S7&Hw-a
literal 0
HcmV?d00001
diff --git a/pystencils_tests/test_data/datahandling_parallel_load_test/src.dat b/pystencils_tests/test_data/datahandling_parallel_load_test/src.dat
new file mode 100644
index 0000000000000000000000000000000000000000..204552486f77c485a4dd333a10eff82f9d44aa9f
GIT binary patch
literal 304
YcmWe&fB*$XC<9D=u!rzQY4mUa0M%S7&Hw-a
literal 0
HcmV?d00001
diff --git a/pystencils_tests/test_data/datahandling_parallel_save_test/dst.dat b/pystencils_tests/test_data/datahandling_parallel_save_test/dst.dat
new file mode 100644
index 0000000000000000000000000000000000000000..204552486f77c485a4dd333a10eff82f9d44aa9f
GIT binary patch
literal 304
YcmWe&fB*$XC<9D=u!rzQY4mUa0M%S7&Hw-a
literal 0
HcmV?d00001
diff --git a/pystencils_tests/test_data/datahandling_parallel_save_test/src.dat b/pystencils_tests/test_data/datahandling_parallel_save_test/src.dat
new file mode 100644
index 0000000000000000000000000000000000000000..204552486f77c485a4dd333a10eff82f9d44aa9f
GIT binary patch
literal 304
YcmWe&fB*$XC<9D=u!rzQY4mUa0M%S7&Hw-a
literal 0
HcmV?d00001
diff --git a/pystencils_tests/test_datahandling.py b/pystencils_tests/test_datahandling.py
index a9b6878c8..57b904e53 100644
--- a/pystencils_tests/test_datahandling.py
+++ b/pystencils_tests/test_datahandling.py
@@ -29,7 +29,7 @@ def basic_iteration(dh):
def access_and_gather(dh, domain_size):
- dh.add_array('f1', dtype=np.dtype(np.int32))
+ dh.add_array('f1', dtype=np.dtype(np.int8))
dh.add_array_like('f2', 'f1')
dh.add_array('v1', values_per_cell=3, dtype=np.int64, ghost_layers=2)
dh.add_array_like('v2', 'v1')
@@ -40,7 +40,7 @@ def access_and_gather(dh, domain_size):
# Check symbolic field properties
assert dh.fields.f1.index_dimensions == 0
assert dh.fields.f1.spatial_dimensions == len(domain_size)
- assert dh.fields.f1.dtype.numpy_dtype == np.int32
+ assert dh.fields.f1.dtype.numpy_dtype == np.int8
assert dh.fields.v1.index_dimensions == 1
assert dh.fields.v1.spatial_dimensions == len(domain_size)
@@ -92,7 +92,7 @@ def synchronization(dh, test_gpu=False):
return
field_name += 'Gpu'
- dh.add_array(field_name, ghost_layers=1, dtype=np.int32, cpu=True, gpu=test_gpu)
+ dh.add_array(field_name, ghost_layers=1, dtype=np.int8, cpu=True, gpu=test_gpu)
# initialize everything with 1
for b in dh.iterate(ghost_layers=1):
@@ -102,8 +102,10 @@ def synchronization(dh, test_gpu=False):
if test_gpu:
dh.to_gpu(field_name)
+ dh.synchronization_function_gpu(field_name)()
+ else:
+ dh.synchronization_function_cpu(field_name)()
- dh.synchronization_function(field_name, target='gpu' if test_gpu else 'cpu')()
if test_gpu:
dh.to_cpu(field_name)
diff --git a/pystencils_tests/test_datahandling_parallel.py b/pystencils_tests/test_datahandling_parallel.py
index efe106dc0..9d9b5f044 100644
--- a/pystencils_tests/test_datahandling_parallel.py
+++ b/pystencils_tests/test_datahandling_parallel.py
@@ -2,10 +2,20 @@ import numpy as np
import waLBerla as wlb
from pystencils import make_slice
+from tempfile import TemporaryDirectory
+from pathlib import Path
+
+from pystencils.boundaries import BoundaryHandling, Neumann
+from pystencils.slicing import slice_from_direction
+
from pystencils.datahandling.parallel_datahandling import ParallelDataHandling
+from pystencils.datahandling import create_data_handling
from pystencils_tests.test_datahandling import (
access_and_gather, kernel_execution_jacobi, reduction, synchronization, vtk_output)
+SCRIPT_FOLDER = Path(__file__).parent.absolute()
+INPUT_FOLDER = SCRIPT_FOLDER / "test_data"
+
try:
import pytest
except ImportError:
@@ -119,3 +129,66 @@ def test_getter_setter():
dh.to_gpu('v')
assert dh.is_on_gpu('v') is True
dh.all_to_cpu()
+
+
+def test_parallel_datahandling_boundary_conditions():
+ pytest.importorskip('waLBerla.cuda')
+ dh = create_data_handling(domain_size=(7, 7), periodicity=True, parallel=True, default_target="gpu")
+ src = dh.add_array('src')
+ src2 = dh.add_array('src2')
+ dh.fill("src", 0.0, ghost_layers=True)
+ dh.fill("src", 1.0, ghost_layers=False)
+ src_cpu = dh.add_array('src_cpu', gpu=False)
+ dh.fill("src_cpu", 0.0, ghost_layers=True)
+ dh.fill("src_cpu", 1.0, ghost_layers=False)
+
+ boundary_stencil = [(1, 0), (-1, 0), (0, 1), (0, -1)]
+ boundary_handling_cpu = BoundaryHandling(dh, src_cpu.name, boundary_stencil,
+ name="boundary_handling_cpu", target='cpu')
+
+ boundary_handling = BoundaryHandling(dh, src.name, boundary_stencil,
+ name="boundary_handling_gpu", target='gpu')
+
+ neumann = Neumann()
+ for d in ('N', 'S', 'W', 'E'):
+ boundary_handling.set_boundary(neumann, slice_from_direction(d, dim=2))
+ boundary_handling_cpu.set_boundary(neumann, slice_from_direction(d, dim=2))
+
+ boundary_handling.prepare()
+ boundary_handling_cpu.prepare()
+
+ boundary_handling_cpu()
+
+ dh.all_to_gpu()
+ boundary_handling()
+ dh.all_to_cpu()
+ for block in dh.iterate():
+ np.testing.assert_almost_equal(block["src_cpu"], block["src"])
+
+ assert dh.custom_data_names == ('boundary_handling_cpuIndexArrays', 'boundary_handling_gpuIndexArrays')
+ dh.swap("src", "src2", gpu=True)
+
+def test_save_data():
+ domain_shape = (2, 2)
+
+ dh = create_data_handling(domain_size=domain_shape, default_ghost_layers=1, parallel=True)
+ dh.add_array("src", values_per_cell=9)
+ dh.fill("src", 1.0, ghost_layers=True)
+ dh.add_array("dst", values_per_cell=9)
+ dh.fill("dst", 1.0, ghost_layers=True)
+
+ dh.save_all(str(INPUT_FOLDER) + '/datahandling_parallel_save_test')
+
+
+def test_load_data():
+ domain_shape = (2, 2)
+
+ dh = create_data_handling(domain_size=domain_shape, default_ghost_layers=1, parallel=True)
+ dh.add_array("src", values_per_cell=9)
+ dh.fill("src", 0.0, ghost_layers=True)
+ dh.add_array("dst", values_per_cell=9)
+ dh.fill("dst", 0.0, ghost_layers=True)
+
+ dh.load_all(str(INPUT_FOLDER) + '/datahandling_parallel_load_test')
+ assert np.all(dh.gather_array('src')) == 1
+ assert np.all(dh.gather_array('src')) == 1
diff --git a/pystencils_tests/test_dot_printer.ipynb b/pystencils_tests/test_dot_printer.ipynb
new file mode 100644
index 000000000..8b61525f5
--- /dev/null
+++ b/pystencils_tests/test_dot_printer.ipynb
@@ -0,0 +1,314 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from pystencils.session import *\n",
+ "from pystencils.astnodes import Block, Conditional"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "src, dst = ps.fields(\"src, dst: double[2D]\", layout='c')\n",
+ "\n",
+ "true_block = Block([ps.Assignment(dst[0, 0], src[-1, 0])])\n",
+ "false_block = Block([ps.Assignment(dst[0, 0], src[1, 0])])\n",
+ "ur = [true_block, Conditional(dst.center() > 0.0, true_block, false_block)]\n",
+ " \n",
+ "ast = ps.create_kernel(ur)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
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+ "</g>\n",
+ "</svg>\n"
+ ],
+ "text/plain": [
+ "<graphviz.files.Source at 0x7f62452c4110>"
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "ps.to_dot(ast, graph_style={'size': \"9.5,12.5\"})"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.7"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/pystencils_tests/test_field.py b/pystencils_tests/test_field.py
index 253ca9f26..1c57e6ecd 100644
--- a/pystencils_tests/test_field.py
+++ b/pystencils_tests/test_field.py
@@ -3,6 +3,8 @@ import pytest
import sympy as sp
import pystencils as ps
+from pystencils import TypedSymbol
+from pystencils.data_types import create_type
from pystencils.field import Field, FieldType, layout_string_to_tuple
@@ -13,11 +15,28 @@ def test_field_basic():
assert f['N'] == f[0, 1]
assert '_' in f.center._latex('dummy')
+ assert f.index_to_physical(index_coordinates=sp.Matrix([0, 0]), staggered=False)[0] == 0
+ assert f.index_to_physical(index_coordinates=sp.Matrix([0, 0]), staggered=False)[1] == 0
+
+ assert f.physical_to_index(physical_coordinates=sp.Matrix([0, 0]), staggered=False)[0] == 0
+ assert f.physical_to_index(physical_coordinates=sp.Matrix([0, 0]), staggered=False)[1] == 0
+
+ f1 = f.new_field_with_different_name("f1")
+ assert f1.ndim == f.ndim
+ assert f1.values_per_cell() == f.values_per_cell()
+
+ fixed = ps.fields("f(5, 5) : double[20, 20]")
+ assert fixed.neighbor_vector((1, 1)).shape == (5, 5)
+
f = Field.create_fixed_size('f', (10, 10), strides=(80, 8), dtype=np.float64)
assert f.spatial_strides == (10, 1)
assert f.index_strides == ()
assert f.center_vector == sp.Matrix([f.center])
+ f1 = f.new_field_with_different_name("f1")
+ assert f1.ndim == f.ndim
+ assert f1.values_per_cell() == f.values_per_cell()
+
f = Field.create_fixed_size('f', (8, 8, 2, 2), index_dimensions=2)
assert f.center_vector == sp.Matrix([[f(0, 0), f(0, 1)],
[f(1, 0), f(1, 1)]])
@@ -138,11 +157,22 @@ def test_staggered():
j1, j2, j3 = ps.fields('j1(2), j2(2,2), j3(2,2,2) : double[2D]', field_type=FieldType.STAGGERED)
assert j1[0, 1](1) == j1.staggered_access((0, sp.Rational(1, 2)))
+ assert j1[0, 1](1) == j1.staggered_access(np.array((0, sp.Rational(1, 2))))
assert j1[1, 1](1) == j1.staggered_access((1, sp.Rational(1, 2)))
assert j1[0, 2](1) == j1.staggered_access((0, sp.Rational(3, 2)))
assert j1[0, 1](1) == j1.staggered_access("N")
assert j1[0, 0](1) == j1.staggered_access("S")
assert j1.staggered_vector_access("N") == sp.Matrix([j1.staggered_access("N")])
+ assert j1.staggered_stencil_name == 'D2Q5'
+
+ assert j1.physical_coordinates[0] == TypedSymbol("ctr_0", create_type("int"), nonnegative=True)
+ assert j1.physical_coordinates[1] == TypedSymbol("ctr_1", create_type("int"), nonnegative=True)
+ assert j1.physical_coordinates_staggered[0] == TypedSymbol("ctr_0", create_type("int"), nonnegative=True) + 0.5
+ assert j1.physical_coordinates_staggered[1] == TypedSymbol("ctr_1", create_type("int"), nonnegative=True) + 0.5
+ assert j1.index_to_physical(index_coordinates=sp.Matrix([0, 0]), staggered=True)[0] == 0.5
+ assert j1.index_to_physical(index_coordinates=sp.Matrix([0, 0]), staggered=True)[1] == 0.5
+ assert j1.physical_to_index(physical_coordinates=sp.Matrix([0, 0]), staggered=True)[0] == -0.5
+ assert j1.physical_to_index(physical_coordinates=sp.Matrix([0, 0]), staggered=True)[1] == -0.5
assert j2[0, 1](1, 1) == j2.staggered_access((0, sp.Rational(1, 2)), 1)
assert j2[0, 1](1, 1) == j2.staggered_access("N", 1)
diff --git a/pystencils_tests/test_finite_differences.py b/pystencils_tests/test_finite_differences.py
index b6d528d17..3ea65267f 100644
--- a/pystencils_tests/test_finite_differences.py
+++ b/pystencils_tests/test_finite_differences.py
@@ -4,7 +4,8 @@ import pytest
import pystencils as ps
from pystencils.astnodes import LoopOverCoordinate
from pystencils.fd import diff, diffusion, Discretization2ndOrder
-from pystencils.fd.spatial import discretize_spatial, fd_stencils_isotropic, fd_stencils_standard
+from pystencils.fd.spatial import discretize_spatial, fd_stencils_isotropic, fd_stencils_standard, \
+ fd_stencils_forth_order_isotropic
def test_spatial_2d_unit_sum():
@@ -18,7 +19,7 @@ def test_spatial_2d_unit_sum():
diff(f, 1, 1),
diff(f, 0, 0) + diff(f, 1, 1)]
- schemes = [fd_stencils_standard, fd_stencils_isotropic]
+ schemes = [fd_stencils_standard, fd_stencils_isotropic, 'standard', 'isotropic']
for term in terms:
for scheme in schemes:
@@ -34,7 +35,7 @@ def test_spatial_1d_unit_sum():
terms = [diff(f, 0),
diff(f, 0, 0)]
- schemes = [fd_stencils_standard, fd_stencils_isotropic]
+ schemes = [fd_stencils_standard, fd_stencils_isotropic, 'standard', 'isotropic']
for term in terms:
for scheme in schemes:
@@ -43,6 +44,17 @@ def test_spatial_1d_unit_sum():
assert sum(coefficients) == 0
+def test_fd_stencils_forth_order_isotropic():
+ f = ps.fields("f: double[2D]")
+ a = fd_stencils_forth_order_isotropic([0], 1, f[0, 0](0))
+ sten, coefficients = ps.stencil.coefficients(a)
+ assert sum(coefficients) == 0
+
+ for i, direction in enumerate(sten):
+ counterpart = sten.index((direction[0] * -1, direction[1] * -1))
+ assert coefficients[i] + coefficients[counterpart] == 0
+
+
def test_staggered_laplacian():
f = ps.fields("f : double[2D]")
a, dx = sp.symbols("a, dx")
diff --git a/pystencils_tests/test_jupyter_extensions.ipynb b/pystencils_tests/test_jupyter_extensions.ipynb
index a34a1bd4f..f0ab21d3e 100644
--- a/pystencils_tests/test_jupyter_extensions.ipynb
+++ b/pystencils_tests/test_jupyter_extensions.ipynb
@@ -39,7 +39,7 @@
{
"data": {
"text/plain": [
- "<matplotlib.image.AxesImage at 0x7f5fa4f1cdc0>"
+ "<matplotlib.image.AxesImage at 0x7fcb7d253710>"
]
},
"execution_count": 4,
@@ -48,9 +48,9 @@
},
{
"data": {
- "image/png": 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\n",
+ "image/png": "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\n",
"text/plain": [
- "<matplotlib.figure.Figure at 0x7f5fa4f425b0>"
+ "<Figure size 1152x432 with 1 Axes>"
]
},
"metadata": {
@@ -80,7 +80,7 @@
"metadata": {},
"outputs": [],
"source": [
- "c_sync = dh.synchronization_function(['c'])"
+ "c_sync = dh.synchronization_function_cpu(['c'])"
]
},
{
@@ -114,7 +114,7 @@
"data": {
"text/html": [
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- " <source 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type=\"video/mp4\">\n",
" Your browser does not support the video tag.\n",
"</video>"
],
@@ -148,9 +148,9 @@
"outputs": [
{
"data": {
- "image/png": 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BCgAAwAgCFQAAgBEEKgAAACMIVAAAAEYQqAAAAIwgUAEAABhBoAIAADCCQAUAAGAEgQoAAMAIAhUAAIARBCoAAAAjCFQAAABGEKgAAACMIFABAAAYQaACAAAwgkAFAABgBIEKAADACAIVAACAEQQqAAAAIwhUAAAARhCoAAAAjCBQAQAAGEGgAgAAMIJABQAAYASBCgAAwAgCFQAAgBEEKgAAACMIVAAAAEYQqAAAAIwgUAEAABhBoAIAADCCQAUAAGAEgQoAAMAIAhUAAIARBCoAAAAjCFQAAABG2LVAraobq+rpqjpSVXfu1vcBAABgNexKoFbVeUl+K8kvJrkyya1VdeVufC8AAABWw269g3pNkiPd/a3u/vMk9ye5aZe+FwAAACtgtwJ1f5JnNj0+uowBAADAlnYrUGuLsf7/dqi6vaoOV9XhEydO7NI0AAAAOFecv0vPezTJ5ZseX5bk2c07dPc9Se5Jkqo6UVV/sktzOZmLkvzp6/w9mcP6r689X/vzLt3L77729nz95zmy1xN4vVj7U6ja6r2FlWL915e1n+Nvns5O1d3b7/UaVdX5Sb6R5Pok30vy5ST/oLufOOvf7AxV1eHuPrTX82BvWP/1Ze3Xm/VfX9Z+vVn/9WXtzz278g5qd79YVe9J8vkk5yW5d1KcAgAAMM9uneKb7v5cks/t1vMDAACwWnbrIknngnv2egLsKeu/vqz9erP+68varzfrv76s/TlmVz6DCgAAAK/VOr+DCgAAwCBrEahV9S+r6utV9dWq+kxV/fVN2+6qqiNV9XRV3bBp/Oer6mvLtn9Ta3D99VVUVTdX1RNV9cOqOvSqbdZ+zVTVjct6H6mqO/d6PpxdVXVvVR2vqsc3jb25qh6qqm8utxdu2rblawDnnqq6vKq+UFVPLa/5713Grf8aqKofqapHqup/Luv/L5Zx678mquq8qvofVfU7y2Nrfw5bi0BN8lCSn+nun83Gn7+5K0mq6soktyS5KsmNST5SVectx3w0ye1JDi5fN77ek+aseDzJ30/yxc2D1n79LOv7W0l+McmVSW5dfg5YHR/PX/59vTPJw919MMnDy+PtXgM497yY5P3d/dNJ3pbkjmWNrf96eCHJ3+7un0tydZIbq+ptsf7r5L1Jntr02Nqfw9YiULv797r7xeXhHye5bLl/U5L7u/uF7v52Nv5a+TVVdWmSH+/uP+qND+n+hyTveN0nzo5191Pd/fQWm6z9+rkmyZHu/lZ3/3mS+7Pxc8CK6O4vJvn+q4ZvSnLfcv++vPL7vOVrwOsyUc667j7W3V9Z7j+fjf9R3R/rvxZ6w/9dHr5x+epY/7VQVZcl+XtJ/v2mYWt/DluLQH2Vf5zkd5f7+5M8s2nb0WVs/3L/1eOsDmu/fk625qy2S7r7WLIRMUkuXsb9PKyoqjqQ5K1JvhTrvzaWUzwfS3I8yUPdbf3Xx79O8s+S/HDTmLU/h+3a30F9vVXV7yf5G1ts+rXu/uyyz69l4zSgT7x82Bb79ynGGeh01n6rw7YYs/arzdqymZ+HFVRVb0ryqSTv6+4fnOISAtZ/xXT3S0muXq4z8pmq+plT7G79V0RV/VKS4939aFVddzqHbDFm7YdZmUDt7l841faqui3JLyW5vl/52zpHk1y+abfLkjy7jF+2xTgDbbf2J2Ht18/J1pzV9lxVXdrdx5ZT+I8v434eVkxVvTEbcfqJ7v70Mmz910x3/5+q+u/Z+Hyh9V991yb55ap6e5IfSfLjVfUfY+3PaWtxim9V3Zjknyf55e7+s02bHkxyS1VdUFVXZOOCOI8spwI8X1VvW67g+o+SnOydOM5N1n79fDnJwaq6oqr+SjYukvDgHs+J3fdgktuW+7flld/nLV8D9mB+nAXL6/XHkjzV3R/etMn6r4Gq2re8c5qq+tEkv5Dk67H+K6+77+ruy7r7QDb+u/4H3f0PY+3PaSvzDuo2/l2SC5I8tJzu88fd/U+6+4mqeiDJk9k49feO5RSRJPmn2bgi5I9m4zOrv/uXnpXxquqdSf5tkn1J/mtVPdbdN1j79dPdL1bVe5J8Psl5Se7t7if2eFqcRVX1ySTXJbmoqo4m+WCSDyV5oKreneS7SW5Okm1eAzj3XJvkXUm+tnwOMUk+EOu/Li5Nct9yNdY3JHmgu3+nqv4o1n9d+d0/h9UrZ7sCAADA3lmLU3wBAACYT6ACAAAwgkAFAABgBIEKAADACAIVAACAEQQqAAAAIwhUAAAARhCoAAAAjPD/AEcCzgpamGVXAAAAAElFTkSuQmCC\n",
+ "image/png": "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\n",
"text/plain": [
- "<matplotlib.figure.Figure at 0x7f5fa4e07160>"
+ "<Figure size 1152x432 with 1 Axes>"
]
},
"metadata": {
@@ -184,9 +184,9 @@
"outputs": [
{
"data": {
- "image/png": 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V1ZvWPaELxH74e9jVpuXTbLFp+7aHbjE2ev17vWH9maw75DvaqPli092PL5enknwuG/+MevK5fVCXy1Prm+HKbbfWi/7voXe5afkkW23ann3y2K9iw/ozWXfIv5bkQFVdX1UvTnI4G5s3X7Sq6qVV9bLnrif502xsXH13kluXw25N8vn1zPC82G6tF/3G3ftl0/LtNm3PPnjs17Jh/QXwCu/bsvGq7neTfGTd8zkP631NNl6h/maSB59bc5JXJDmW5DvL5RXrnuserfcz2fhn5C+y8czjPWdaa5KPLH8LjyR567rnv4K1/2OSbyW5f/kP+OqLdO1/lI3TA/cnuW/5ett+eOzPsPaVPfY+2Qkw3LpPrQCwS0IOMJyQAwwn5ADDCTnAcEIOMJyQAwwn5ADD/S+qRf44PxPM0QAAAABJRU5ErkJggg==\n",
+ "image/png": "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\n",
"text/plain": [
- "<matplotlib.figure.Figure at 0x7f5fc03ea6a0>"
+ "<Figure size 1152x432 with 1 Axes>"
]
},
"metadata": {
@@ -198,6 +198,18 @@
"source": [
"animation = ps.jupyter.make_imshow_animation(dh.cpu_arrays[\"c\"], grid_update_function, frames=300)"
]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ps.jupyter.set_display_mode(\"video\")\n",
+ "ps.jupyter.set_display_mode(\"window\")\n",
+ "ps.jupyter.set_display_mode(\"image_update\")\n",
+ "ps.jupyter.activate_ipython()"
+ ]
}
],
"metadata": {
@@ -216,7 +228,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.5"
+ "version": "3.7.7"
}
},
"nbformat": 4,
diff --git a/pystencils_tests/test_kerncraft_coupling.py b/pystencils_tests/test_kerncraft_coupling.py
index 533cc954e..0f282fd11 100644
--- a/pystencils_tests/test_kerncraft_coupling.py
+++ b/pystencils_tests/test_kerncraft_coupling.py
@@ -7,7 +7,7 @@ from kerncraft.kernel import KernelCode
from kerncraft.machinemodel import MachineModel
from kerncraft.models import ECM, ECMData, Benchmark
-from pystencils import Assignment, Field, fields
+from pystencils import Assignment, Field
from pystencils.cpu import create_kernel
from pystencils.kerncraft_coupling import KerncraftParameters, PyStencilsKerncraftKernel
from pystencils.kerncraft_coupling.generate_benchmark import generate_benchmark, run_c_benchmark
@@ -47,8 +47,6 @@ def analysis(kernel, machine, model='ecmdata'):
model = ECMData(kernel, machine, KerncraftParameters())
elif model == 'ecm':
model = ECM(kernel, machine, KerncraftParameters())
- # model.analyze()
- # model.plot()
elif model == 'benchmark':
model = Benchmark(kernel, machine, KerncraftParameters())
else:
@@ -79,10 +77,17 @@ def test_3d_7pt_osaca():
update_rule = Assignment(b[0, 0, 0], s * rhs)
ast = create_kernel([update_rule])
- k = PyStencilsKerncraftKernel(ast, machine=machine_model)
+ k = PyStencilsKerncraftKernel(ast, machine=machine_model, debug_print=True)
analysis(k, machine_model, model='ecm')
assert reference_kernel._flops == k._flops
- # assert reference.results['cl throughput'] == analysis.results['cl throughput']
+
+ path, lock = k.get_kernel_code(openmp=True)
+ with open(path) as kernel_file:
+ assert "#pragma omp parallel" in kernel_file.read()
+
+ path, lock = k.get_main_code()
+ with open(path) as kernel_file:
+ assert "likwid_markerInit();" in kernel_file.read()
@pytest.mark.kerncraft
diff --git a/pystencils_tests/test_llvm.py b/pystencils_tests/test_llvm.py
index 54c60ff45..1337d3041 100644
--- a/pystencils_tests/test_llvm.py
+++ b/pystencils_tests/test_llvm.py
@@ -138,5 +138,131 @@ def test_pow_llvm():
assert np.all(256.0 == dst_field_llvm)
+def test_piecewise_llvm():
+ size = (30, 20)
+
+ src_field_llvm = np.zeros(size)
+ dst_field_llvm = np.zeros(size)
+
+ src_field_llvm[0:15, :] = 10.0
+
+ f = Field.create_from_numpy_array("f", src_field_llvm)
+ d = Field.create_from_numpy_array("d", dst_field_llvm)
+
+ picewise_test_strict_less_than = Assignment(d[0, 0], sp.Piecewise((1.0, f[0, 0] > 10), (0.0, True)))
+ ast = create_kernel([picewise_test_strict_less_than])
+
+ jit = generate_and_jit(ast)
+ jit('kernel', dst_field_llvm, src_field_llvm)
+
+ assert (np.all(dst_field_llvm[:, :] == 0.0))
+
+ src_field_llvm = np.zeros(size)
+ dst_field_llvm = np.zeros(size)
+
+ src_field_llvm[0:15, :] = 10.0
+
+ picewise_test_less_than = Assignment(d[0, 0], sp.Piecewise((1.0, f[0, 0] >= 10), (0.0, True)))
+ ast = create_kernel([picewise_test_less_than])
+
+ jit = generate_and_jit(ast)
+ jit('kernel', dst_field_llvm, src_field_llvm)
+
+ assert (np.all(dst_field_llvm[0:15, :] == 1.0))
+
+ src_field_llvm = np.zeros(size)
+ dst_field_llvm = np.zeros(size)
+
+ src_field_llvm[0:15, :] = 10.0
+
+ picewise_test_strict_greater_than = Assignment(d[0, 0], sp.Piecewise((1.0, f[0, 0] < 5), (0.0, True)))
+ ast = create_kernel([picewise_test_strict_greater_than])
+
+ jit = generate_and_jit(ast)
+ jit('kernel', dst_field_llvm, src_field_llvm)
+
+ assert (np.all(dst_field_llvm[15:, :] == 1.0))
+
+ src_field_llvm = np.zeros(size)
+ dst_field_llvm = np.zeros(size)
+
+ src_field_llvm[0:15, :] = 10.0
+
+ picewise_test_greater_than = Assignment(d[0, 0], sp.Piecewise((1.0, f[0, 0] <= 10), (0.0, True)))
+ ast = create_kernel([picewise_test_greater_than])
+
+ jit = generate_and_jit(ast)
+ jit('kernel', dst_field_llvm, src_field_llvm)
+
+ assert (np.all(dst_field_llvm[:, :] == 1.0))
+
+ src_field_llvm = np.zeros(size)
+ dst_field_llvm = np.zeros(size)
+
+ src_field_llvm[0:15, :] = 10.0
+
+ picewise_test_equality = Assignment(d[0, 0], sp.Piecewise((1.0, sp.Equality(f[0, 0], 10.0)), (0.0, True)))
+ ast = create_kernel([picewise_test_equality])
+
+ jit = generate_and_jit(ast)
+ jit('kernel', dst_field_llvm, src_field_llvm)
+
+ assert (np.all(dst_field_llvm[0:15, :] == 1.0))
+
+ src_field_llvm = np.zeros(size)
+ dst_field_llvm = np.zeros(size)
+
+ src_field_llvm[0:15, :] = 10.0
+
+ picewise_test_unequality = Assignment(d[0, 0], sp.Piecewise((1.0, sp.Unequality(f[0, 0], 10.0)), (0.0, True)))
+ ast = create_kernel([picewise_test_unequality])
+
+ jit = generate_and_jit(ast)
+ jit('kernel', dst_field_llvm, src_field_llvm)
+
+ assert (np.all(dst_field_llvm[15:, :] == 1.0))
+
+
+def test_piecewise_or_llvm():
+ size = (30, 20)
+
+ src_field_llvm = np.zeros(size)
+ dst_field_llvm = np.zeros(size)
+
+ src_field_llvm[0:15, :] = 10.5
+
+ f = Field.create_from_numpy_array("f", src_field_llvm)
+ d = Field.create_from_numpy_array("d", dst_field_llvm)
+
+ picewise_test_or = Assignment(d[0, 0], sp.Piecewise((1.0, sp.Or(f[0, 0] > 11, f[0, 0] < 10)), (0.0, True)))
+ ast = create_kernel([picewise_test_or])
+
+ jit = generate_and_jit(ast)
+ jit('kernel', dst_field_llvm, src_field_llvm)
+
+ assert (np.all(dst_field_llvm[0:15, :] == 0.0))
+
+
+def test_print_function_llvm():
+ size = (30, 20)
+
+ src_field_llvm = np.zeros(size)
+ dst_field_llvm = np.zeros(size)
+
+ src_field_llvm[0:15, :] = 0.0
+
+ f = Field.create_from_numpy_array("f", src_field_llvm)
+ d = Field.create_from_numpy_array("d", dst_field_llvm)
+
+ up = Assignment(d[0, 0], sp.sin(f[0, 0]))
+ ast = create_kernel([up])
+
+ # kernel = make_python_function(ast, {'f': src_field_llvm, 'd': dst_field_llvm})
+ jit = generate_and_jit(ast)
+ jit('kernel', dst_field_llvm, src_field_llvm)
+
+ assert (np.all(dst_field_llvm[:, :] == 0.0))
+
+
if __name__ == "__main__":
test_jacobi_fixed_field_size_gpu()
diff --git a/pystencils_tests/test_loop_cutting.py b/pystencils_tests/test_loop_cutting.py
index daf803cbd..53411715a 100644
--- a/pystencils_tests/test_loop_cutting.py
+++ b/pystencils_tests/test_loop_cutting.py
@@ -80,6 +80,7 @@ def test_staggered_iteration_manual():
counters = [LoopOverCoordinate.get_loop_counter_symbol(i) for i in range(dim)]
conditions = [counters[i] < f.shape[i] - 1 for i in range(dim)]
+ conditions2 = counters[0] > f.shape[0] + 5
for d in range(dim):
eq = SympyAssignment(s(d), sum(f[o] for o in offsets_in_plane(d, 0, dim)) -
@@ -87,6 +88,11 @@ def test_staggered_iteration_manual():
cond = sp.And(*[conditions[i] for i in range(dim) if d != i])
eqs.append(Conditional(cond, eq))
+ # this conditional should vanish entirely because it is never true
+ eq = SympyAssignment(s(0), f[0, 0])
+ cond = sp.And(*[conditions2])
+ eqs.append(Conditional(cond, eq))
+
kernel_ast = create_kernel(eqs, ghost_layers=[(1, 0), (1, 0), (1, 0)])
func = make_python_function(kernel_ast)
diff --git a/pystencils_tests/test_stencil_plot.ipynb b/pystencils_tests/test_stencil_plot.ipynb
new file mode 100644
index 000000000..aea27c8a9
--- /dev/null
+++ b/pystencils_tests/test_stencil_plot.ipynb
@@ -0,0 +1,62 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pystencils as ps\n",
+ "import sympy as sp\n",
+ "\n",
+ "from pystencils.stencil import coefficient_list, plot_expression, plot"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "sten = ((0, 0, 0), (1, 0, 0), (0, 1, 0), (0, 0, 1),\n",
+ " (-1, 0, 0), (0, -1, 0), (0, 0, -1))\n",
+ "\n",
+ "plot(sten)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.7"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/pystencils_tests/test_sympy_optimizations.py b/pystencils_tests/test_sympy_optimizations.py
index e33278b4f..8262cfc1c 100644
--- a/pystencils_tests/test_sympy_optimizations.py
+++ b/pystencils_tests/test_sympy_optimizations.py
@@ -2,28 +2,32 @@ import pytest
import sympy as sp
import pystencils
-from pystencils.math_optimizations import HAS_REWRITING, optimize_assignments, optims_pystencils_cpu
+from pystencils.math_optimizations import HAS_REWRITING, optimize_assignments, optims_pystencils_cpu, optimize_ast
@pytest.mark.skipif(not HAS_REWRITING, reason="need sympy.codegen.rewriting")
def test_sympy_optimizations():
for target in ('cpu', 'gpu'):
- x, y, z = pystencils.fields('x, y, z: float32[2d]')
-
- # Triggers Sympy's expm1 optimization
- # Sympy's expm1 optimization is tedious to use and the behaviour is highly depended on the sympy version. In
- # some cases the exp expression has to be encapsulated in brackets or multiplied with 1 or 1.0
- # for sympy to work properly ...
- assignments = pystencils.AssignmentCollection({
- x[0, 0]: 1.0 * (sp.exp(y[0, 0]) - 1)
- })
-
- assignments = optimize_assignments(assignments, optims_pystencils_cpu)
- print(assignments)
-
- ast = pystencils.create_kernel(assignments, target=target)
- code = pystencils.get_code_str(ast)
- assert 'expm1(' in code
+ for op_ast in (True, False):
+ x, y, z = pystencils.fields('x, y, z: float32[2d]')
+
+ # Triggers Sympy's expm1 optimization
+ # Sympy's expm1 optimization is tedious to use and the behaviour is highly depended on the sympy version. In
+ # some cases the exp expression has to be encapsulated in brackets or multiplied with 1 or 1.0
+ # for sympy to work properly ...
+ assignments = pystencils.AssignmentCollection({
+ x[0, 0]: 1.0 * (sp.exp(y[0, 0]) - 1)
+ })
+
+ if not op_ast:
+ assignments = optimize_assignments(assignments, optims_pystencils_cpu)
+ print(assignments)
+
+ ast = pystencils.create_kernel(assignments, target=target)
+ if op_ast:
+ optimize_ast(ast, optims_pystencils_cpu)
+ code = pystencils.get_code_str(ast)
+ assert 'expm1(' in code
@pytest.mark.skipif(not HAS_REWRITING, reason="need sympy.codegen.rewriting")
diff --git a/pystencils_tests/test_sympyextensions.py b/pystencils_tests/test_sympyextensions.py
index 2135ee88e..82e0ef402 100644
--- a/pystencils_tests/test_sympyextensions.py
+++ b/pystencils_tests/test_sympyextensions.py
@@ -1,4 +1,5 @@
import sympy
+import numpy as np
import pystencils
from pystencils.sympyextensions import replace_second_order_products
@@ -8,12 +9,33 @@ from pystencils.sympyextensions import extract_most_common_factor
from pystencils.sympyextensions import count_operations
from pystencils.sympyextensions import common_denominator
from pystencils.sympyextensions import get_symmetric_part
+from pystencils.sympyextensions import scalar_product
+from pystencils.sympyextensions import kronecker_delta
from pystencils import Assignment
from pystencils.fast_approximation import (fast_division, fast_inv_sqrt, fast_sqrt,
insert_fast_divisions, insert_fast_sqrts)
+def test_utility():
+ a = [1, 2]
+ b = (2, 3)
+
+ a_np = np.array(a)
+ b_np = np.array(b)
+ assert scalar_product(a, b) == np.dot(a_np, b_np)
+
+ a = sympy.Symbol("a")
+ b = sympy.Symbol("b")
+
+ assert kronecker_delta(a, a, a, b) == 0
+ assert kronecker_delta(a, a, a, a) == 1
+ assert kronecker_delta(3, 3, 3, 2) == 0
+ assert kronecker_delta(2, 2, 2, 2) == 1
+ assert kronecker_delta([10] * 100) == 1
+ assert kronecker_delta((0, 1), (0, 1)) == 1
+
+
def test_replace_second_order_products():
x, y = sympy.symbols('x y')
expr = 4 * x * y
@@ -35,6 +57,8 @@ def test_replace_second_order_products():
replace_second_order_products(expr, search_symbols=[x, y], positive=True, replace_mixed=a)
assert len(a) == 2
+ assert replace_second_order_products(4 + y, search_symbols=[x, y]) == y + 4
+
def test_remove_higher_order_terms():
x, y = sympy.symbols('x y')
@@ -97,6 +121,20 @@ def test_count_operations():
assert ops['divs'] == 1
assert ops['sqrts'] == 1
+ expr = 1 / sympy.sqrt(z)
+ ops = count_operations(expr, only_type=None)
+ assert ops['adds'] == 0
+ assert ops['muls'] == 0
+ assert ops['divs'] == 1
+ assert ops['sqrts'] == 1
+
+ expr = sympy.Rel(1 / sympy.sqrt(z), 5)
+ ops = count_operations(expr, only_type=None)
+ assert ops['adds'] == 0
+ assert ops['muls'] == 0
+ assert ops['divs'] == 1
+ assert ops['sqrts'] == 1
+
expr = sympy.sqrt(x + y)
expr = insert_fast_sqrts(expr).atoms(fast_sqrt)
ops = count_operations(*expr, only_type=None)
diff --git a/pystencils_tests/test_transformations.py b/pystencils_tests/test_transformations.py
new file mode 100644
index 000000000..9b0024980
--- /dev/null
+++ b/pystencils_tests/test_transformations.py
@@ -0,0 +1,25 @@
+import pystencils as ps
+from pystencils import TypedSymbol
+from pystencils.astnodes import LoopOverCoordinate, SympyAssignment
+from pystencils.data_types import create_type
+from pystencils.transformations import filtered_tree_iteration, get_loop_hierarchy, get_loop_counter_symbol_hierarchy
+
+
+def test_loop_information():
+ f, g = ps.fields("f, g: double[2D]")
+ update_rule = ps.Assignment(g[0, 0], f[0, 0])
+
+ ast = ps.create_kernel(update_rule)
+ inner_loops = [l for l in filtered_tree_iteration(ast, LoopOverCoordinate, stop_type=SympyAssignment)
+ if l.is_innermost_loop]
+
+ loop_order = []
+ for i in get_loop_hierarchy(inner_loops[0].args[0]):
+ loop_order.append(i)
+
+ assert loop_order == [0, 1]
+
+ loop_symbols = get_loop_counter_symbol_hierarchy(inner_loops[0].args[0])
+
+ assert loop_symbols == [TypedSymbol("ctr_1", create_type("int"), nonnegative=True),
+ TypedSymbol("ctr_0", create_type("int"), nonnegative=True)]
diff --git a/pystencils_tests/test_types.py b/pystencils_tests/test_types.py
index 4deb69acd..381130f06 100644
--- a/pystencils_tests/test_types.py
+++ b/pystencils_tests/test_types.py
@@ -1,8 +1,12 @@
import sympy as sp
import numpy as np
+import pytest
+import ctypes
+
import pystencils as ps
from pystencils import data_types
-from pystencils.data_types import TypedSymbol, get_type_of_expression, VectorType, collate_types, create_type
+from pystencils.data_types import TypedSymbol, get_type_of_expression, VectorType, collate_types, create_type,\
+ typed_symbols, type_all_numbers, matrix_symbols, cast_func, pointer_arithmetic_func, ctypes_from_llvm, PointerType
def test_parsing():
@@ -24,6 +28,33 @@ def test_collation():
assert collate_types([double4_type, float4_type]) == double4_type
+def test_vector_type():
+ double_type = create_type("double")
+ float_type = create_type("float32")
+ double4_type = VectorType(double_type, 4)
+ float4_type = VectorType(float_type, 4)
+
+ assert double4_type.item_size == 4
+ assert float4_type.item_size == 4
+
+ assert not double4_type == 4
+
+
+def test_pointer_type():
+ double_type = create_type("double")
+ float_type = create_type("float32")
+ double4_type = PointerType(double_type, restrict=True)
+ float4_type = PointerType(float_type, restrict=False)
+
+ assert double4_type.item_size == 1
+ assert float4_type.item_size == 1
+
+ assert not double4_type == 4
+
+ assert not double4_type.alias
+ assert float4_type.alias
+
+
def test_dtype_of_constants():
# Some come constants are neither of type Integer,Float,Rational and don't have args
# >>> isinstance(pi, Integer)
@@ -60,3 +91,77 @@ def test_sqrt_of_integer():
kernel = ps.create_kernel(assignments).compile()
kernel(f=arr)
assert 1.7 < arr[0] < 1.8
+
+
+def test_integer_comparision():
+ f = ps.fields("f [2D]")
+ d = sp.Symbol("dir")
+
+ ur = ps.Assignment(f[0, 0], sp.Piecewise((0, sp.Equality(d, 1)), (f[0, 0], True)))
+
+ ast = ps.create_kernel(ur)
+ code = ps.get_code_str(ast)
+
+ assert "_data_f_00[_stride_f_1*ctr_1] = ((((dir) == (1))) ? (0.0): (_data_f_00[_stride_f_1*ctr_1]));" in code
+
+
+def test_Basic_data_type():
+ assert typed_symbols(("s", "f"), np.uint) == typed_symbols("s, f", np.uint)
+ t_symbols = typed_symbols(("s", "f"), np.uint)
+ s = t_symbols[0]
+
+ assert t_symbols[0] == TypedSymbol("s", np.uint)
+ assert s.dtype.is_uint()
+ assert s.dtype.is_complex() == 0
+
+ assert typed_symbols(("s"), np.str).dtype.is_other()
+ assert typed_symbols(("s"), np.bool).dtype.is_other()
+ assert typed_symbols(("s"), np.void).dtype.is_other()
+
+ assert typed_symbols(("s"), np.float64).dtype.base_name == 'double'
+ # removed for old sympy version
+ # assert typed_symbols(("s"), np.float64).dtype.sympy_dtype == typed_symbols(("s"), float).dtype.sympy_dtype
+
+ f, g = ps.fields("f, g : double[2D]")
+
+ expr = ps.Assignment(f.center(), 2 * g.center() + 5)
+ new_expr = type_all_numbers(expr, np.float64)
+
+ assert "cast_func(2, double)" in str(new_expr)
+ assert "cast_func(5, double)" in str(new_expr)
+
+ m = matrix_symbols("a, b", np.uint, 3, 3)
+ assert len(m) == 2
+ m = m[0]
+ for i, elem in enumerate(m):
+ assert elem == TypedSymbol(f"a{i}", np.uint)
+ assert elem.dtype.is_uint()
+
+ assert TypedSymbol("s", np.uint).canonical == TypedSymbol("s", np.uint)
+ assert TypedSymbol("s", np.uint).reversed == TypedSymbol("s", np.uint)
+
+
+def test_cast_func():
+ assert cast_func(TypedSymbol("s", np.uint), np.int64).canonical == TypedSymbol("s", np.uint).canonical
+
+ a = cast_func(5, np.uint)
+ assert a.is_negative is False
+ assert a.is_nonnegative
+
+
+def test_pointer_arithmetic_func():
+ assert pointer_arithmetic_func(TypedSymbol("s", np.uint), 1).canonical == TypedSymbol("s", np.uint).canonical
+
+
+def test_ctypes_from_llvm():
+ pytest.importorskip('llvmlite')
+ import llvmlite.ir as ir
+
+ ctypes_from_llvm(ir.VoidType())
+ assert ctypes_from_llvm(ir.IntType(8)) == ctypes.c_int8
+ assert ctypes_from_llvm(ir.IntType(16)) == ctypes.c_int16
+ assert ctypes_from_llvm(ir.IntType(32)) == ctypes.c_int32
+ assert ctypes_from_llvm(ir.IntType(64)) == ctypes.c_int64
+
+ assert ctypes_from_llvm(ir.FloatType()) == ctypes.c_float
+ assert ctypes_from_llvm(ir.DoubleType()) == ctypes.c_double
diff --git a/pystencils_tests/test_vectorization.py b/pystencils_tests/test_vectorization.py
index f40a1875a..640b8919a 100644
--- a/pystencils_tests/test_vectorization.py
+++ b/pystencils_tests/test_vectorization.py
@@ -13,6 +13,7 @@ if supported_instruction_sets:
else:
instruction_set = None
+
def test_vector_type_propagation():
a, b, c, d, e = sp.symbols("a b c d e")
arr = np.ones((2 ** 2 + 2, 2 ** 3 + 2))
@@ -32,6 +33,42 @@ def test_vector_type_propagation():
np.testing.assert_equal(dst[1:-1, 1:-1], 2 * 10.0 + 3)
+def test_vectorized_abs():
+ arr = np.ones((2 ** 2 + 2, 2 ** 3 + 2))
+ arr[-3:, :] = -1
+
+ f, g = ps.fields(f=arr, g=arr)
+ update_rule = [ps.Assignment(g.center(), sp.Abs(f.center()))]
+
+ ast = ps.create_kernel(update_rule)
+ vectorize(ast, instruction_set=instruction_set)
+
+ func = ast.compile()
+ dst = np.zeros_like(arr)
+ func(g=dst, f=arr)
+ np.testing.assert_equal(np.sum(dst[1:-1, 1:-1]), 2 ** 2 * 2 ** 3)
+
+
+def test_aligned_and_nt_stores():
+ domain_size = (24, 24)
+ # create a datahandling object
+ dh = ps.create_data_handling(domain_size, periodicity=(True, True), parallel=False, default_target='cpu')
+
+ # fields
+ g = dh.add_array("g", values_per_cell=1, alignment=True)
+ dh.fill("g", 1.0, ghost_layers=True)
+ f = dh.add_array("f", values_per_cell=1, alignment=True)
+ dh.fill("f", 0.0, ghost_layers=True)
+ opt = {'instruction_set': instruction_set, 'assume_aligned': True, 'nontemporal': True,
+ 'assume_inner_stride_one': True}
+ update_rule = [ps.Assignment(f.center(), 0.25 * (g[-1, 0] + g[1, 0] + g[0, -1] + g[0, 1]))]
+ ast = ps.create_kernel(update_rule, target=dh.default_target, cpu_vectorize_info=opt)
+ kernel = ast.compile()
+
+ dh.run_kernel(kernel)
+ np.testing.assert_equal(np.sum(dh.cpu_arrays['f']), np.prod(domain_size))
+
+
def test_inplace_update():
shape = (9, 9, 3)
arr = np.ones(shape, order='f')
diff --git a/pystencils_tests/test_vectorization_specific.py b/pystencils_tests/test_vectorization_specific.py
index 6764f282b..d5727d40f 100644
--- a/pystencils_tests/test_vectorization_specific.py
+++ b/pystencils_tests/test_vectorization_specific.py
@@ -1,14 +1,9 @@
import pytest
import numpy as np
-import sympy as sp
import pystencils as ps
from pystencils.backends.simd_instruction_sets import get_supported_instruction_sets
-from pystencils.cpu.vectorization import vectorize
-from pystencils.fast_approximation import insert_fast_sqrts, insert_fast_divisions
-from pystencils.transformations import replace_inner_stride_with_one
-from pystencils.backends.simd_instruction_sets import get_supported_instruction_sets
supported_instruction_sets = get_supported_instruction_sets() if get_supported_instruction_sets() else []
diff --git a/pytest.ini b/pytest.ini
index 0cf6fbee5..e7b0eeb98 100644
--- a/pytest.ini
+++ b/pytest.ini
@@ -41,7 +41,7 @@ exclude_lines =
if __name__ == .__main__.:
skip_covered = True
-fail_under = 85
+fail_under = 89
[html]
directory = coverage_report
--
GitLab