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patricksnape/The Power of Sqrt.ipynb

Created March 7, 2016 19:31
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The Power of Sqrt.ipynb
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"source": "%load_ext cython",
"execution_count": 1,
"outputs": []
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"source": "import math\nimport numpy as np\nfrom numpy.lib import pad\n\n\nindata = np.random.rand(1400,1600)\noutdata = np.zeros(shape=indata.shape, dtype='float64') \n\n\nprint(\"shape before\", indata.shape)\nindata = pad(indata, (1, 1), 'reflect', reflect_type='odd') # allow edge calcs\nprint(\"shape after\", indata.shape)",
"execution_count": 2,
"outputs": [
{
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"text": "('shape before', (1400, 1600))\n('shape after', (1402, 1602))\n",
"name": "stdout"
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"source": "def slope(indata, outdata):\n I = outdata.shape[0]\n J = outdata.shape[1]\n for i in range(I):\n for j in range(J):\n # percent slope using Zevenbergen-Thorne method\n # assume edges added, inarr is offset by one on both axes cmp to outarr\n dzdx = (indata[i+1, j] - indata[i+1, j+2]) / 2 # assume cellsize == one unit, otherwise (2 * cellsize)\n dzdy = (indata[i, j+1] - indata[i+2, j+1]) / 2\n slp = math.sqrt((dzdx * dzdx) + (dzdy * dzdy)) * 100 # percent slope (take math.atan to get angle)\n outdata[i, j] = slp\n \ndef reset_outdata():\n outdata = np.zeros(shape=indata.shape, dtype='float64')",
"execution_count": 3,
"outputs": []
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"cell_type": "code",
"source": "reset_outdata()\n%timeit slope(indata, outdata)",
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"text": "1 loop, best of 3: 4.07 s per loop\n",
"name": "stdout"
}
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"source": "%%cython -a\nimport cython\n\[email protected](False)\ndef slope_cython_pow(double [:, :] indata, double [:, :] outdata):\n cdef int I, J\n cdef int i, j, x\n cdef double k, slp, dzdx, dzdy\n I = outdata.shape[0]\n J = outdata.shape[1]\n for i in range(I):\n for j in range(J):\n dzdx = (indata[i+1, j] - indata[i+1, j+2]) / 2\n dzdy = (indata[i, j+1] - indata[i+2, j+1]) / 2\n k = (dzdx * dzdx) + (dzdy * dzdy)\n slp = k ** 0.5 * 100\n outdata[i, j] = slp",
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/*proto*/\nstatic PyMethodDef __pyx_mdef_46_cython_magic_7246891f750af146da65822ff54f4244_1slope_cython_pow = {\"slope_cython_pow\", (PyCFunction)__pyx_pw_46_cython_magic_7246891f750af146da65822ff54f4244_1slope_cython_pow, METH_VARARGS|METH_KEYWORDS, 0};\nstatic PyObject *__pyx_pw_46_cython_magic_7246891f750af146da65822ff54f4244_1slope_cython_pow(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {\n __Pyx_memviewslice __pyx_v_indata = { 0, 0, { 0 }, { 0 }, { 0 } };\n __Pyx_memviewslice __pyx_v_outdata = { 0, 0, { 0 }, { 0 }, { 0 } };\n PyObject *__pyx_r = 0;\n <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"slope_cython_pow (wrapper)\", 0);\n {\n static PyObject **__pyx_pyargnames[] = {&amp;__pyx_n_s_indata,&amp;__pyx_n_s_outdata,0};\n PyObject* values[2] = {0,0};\n if (unlikely(__pyx_kwds)) {\n Py_ssize_t kw_args;\n const Py_ssize_t pos_args = <span 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__pyx_clineno = 0;\n\n /* function exit code */\n <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n return __pyx_r;\n}\n\nstatic PyObject *__pyx_pf_46_cython_magic_7246891f750af146da65822ff54f4244_slope_cython_pow(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_indata, __Pyx_memviewslice __pyx_v_outdata) {\n int __pyx_v_I;\n int __pyx_v_J;\n int __pyx_v_i;\n int __pyx_v_j;\n double __pyx_v_k;\n double __pyx_v_slp;\n double __pyx_v_dzdx;\n double __pyx_v_dzdy;\n PyObject *__pyx_r = NULL;\n <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"slope_cython_pow\", 0);\n/* … */\n /* function exit code */\n __pyx_r = Py_None; <span class='pyx_macro_api'>__Pyx_INCREF</span>(Py_None);\n __PYX_XDEC_MEMVIEW(&amp;__pyx_v_indata, 1);\n __PYX_XDEC_MEMVIEW(&amp;__pyx_v_outdata, 1);\n <span class='refnanny'>__Pyx_XGIVEREF</span>(__pyx_r);\n <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n return __pyx_r;\n}\n/* … */\n __pyx_tuple__14 = <span class='py_c_api'>PyTuple_Pack</span>(11, __pyx_n_s_indata, __pyx_n_s_outdata, __pyx_n_s_I, __pyx_n_s_J, __pyx_n_s_i, __pyx_n_s_j, __pyx_n_s_x, __pyx_n_s_k, __pyx_n_s_slp, __pyx_n_s_dzdx, __pyx_n_s_dzdy);<span class='error_goto'> if (unlikely(!__pyx_tuple__14)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 4; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_tuple__14);\n <span class='refnanny'>__Pyx_GIVEREF</span>(__pyx_tuple__14);\n/* … */\n __pyx_t_1 = PyCFunction_NewEx(&amp;__pyx_mdef_46_cython_magic_7246891f750af146da65822ff54f4244_1slope_cython_pow, NULL, __pyx_n_s_cython_magic_7246891f750af146da);<span class='error_goto'> if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 4; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_t_1);\n if (<span class='py_c_api'>PyDict_SetItem</span>(__pyx_d, __pyx_n_s_slope_cython_pow, __pyx_t_1) &lt; 0) <span class='error_goto'>{__pyx_filename = __pyx_f[0]; __pyx_lineno = 4; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='pyx_macro_api'>__Pyx_DECREF</span>(__pyx_t_1); __pyx_t_1 = 0;\n __pyx_codeobj__15 = (PyObject*)<span class='pyx_c_api'>__Pyx_PyCode_New</span>(2, 0, 11, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__14, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_pts08_cache_ipython_cython, __pyx_n_s_slope_cython_pow, 4, __pyx_empty_bytes);<span class='error_goto'> if (unlikely(!__pyx_codeobj__15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 4; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">05</span>: <span class=\"k\">cdef</span> <span class=\"kt\">int</span> <span class=\"nf\">I</span><span class=\"p\">,</span> <span class=\"nf\">J</span></pre>\n<pre class=\"cython line score-0\">&#xA0;<span class=\"\">06</span>: <span class=\"k\">cdef</span> <span class=\"kt\">int</span> <span class=\"nf\">i</span><span class=\"p\">,</span> <span class=\"nf\">j</span><span class=\"p\">,</span> <span class=\"nf\">x</span></pre>\n<pre class=\"cython line score-0\">&#xA0;<span class=\"\">07</span>: <span class=\"k\">cdef</span> <span class=\"kt\">double</span> <span class=\"nf\">k</span><span class=\"p\">,</span> <span class=\"nf\">slp</span><span class=\"p\">,</span> <span class=\"nf\">dzdx</span><span class=\"p\">,</span> <span class=\"nf\">dzdy</span></pre>\n<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">08</span>: <span class=\"n\">I</span> <span class=\"o\">=</span> <span class=\"n\">outdata</span><span class=\"o\">.</span><span class=\"n\">shape</span><span class=\"p\">[</span><span class=\"mf\">0</span><span class=\"p\">]</span></pre>\n<pre class='cython code score-0 '> __pyx_v_I = (__pyx_v_outdata.shape[0]);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">09</span>: <span class=\"n\">J</span> <span class=\"o\">=</span> <span class=\"n\">outdata</span><span class=\"o\">.</span><span class=\"n\">shape</span><span class=\"p\">[</span><span class=\"mf\">1</span><span class=\"p\">]</span></pre>\n<pre class='cython code score-0 '> __pyx_v_J = (__pyx_v_outdata.shape[1]);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">10</span>: <span class=\"k\">for</span> <span class=\"n\">i</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"n\">I</span><span class=\"p\">):</span></pre>\n<pre class='cython code score-0 '> __pyx_t_1 = __pyx_v_I;\n for (__pyx_t_2 = 0; __pyx_t_2 &lt; __pyx_t_1; __pyx_t_2+=1) {\n __pyx_v_i = __pyx_t_2;\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">11</span>: <span class=\"k\">for</span> <span class=\"n\">j</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"n\">J</span><span class=\"p\">):</span></pre>\n<pre class='cython code score-0 '> __pyx_t_3 = __pyx_v_J;\n for (__pyx_t_4 = 0; __pyx_t_4 &lt; __pyx_t_3; __pyx_t_4+=1) {\n __pyx_v_j = __pyx_t_4;\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">12</span>: <span class=\"n\">dzdx</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">2</span><span class=\"p\">])</span> <span class=\"o\">/</span> <span class=\"mf\">2</span></pre>\n<pre class='cython code score-0 '> __pyx_t_5 = (__pyx_v_i + 1);\n __pyx_t_6 = __pyx_v_j;\n if (__pyx_t_5 &lt; 0) __pyx_t_5 += __pyx_v_indata.shape[0];\n if (__pyx_t_6 &lt; 0) __pyx_t_6 += __pyx_v_indata.shape[1];\n __pyx_t_7 = (__pyx_v_i + 1);\n __pyx_t_8 = (__pyx_v_j + 2);\n if (__pyx_t_7 &lt; 0) __pyx_t_7 += __pyx_v_indata.shape[0];\n if (__pyx_t_8 &lt; 0) __pyx_t_8 += __pyx_v_indata.shape[1];\n __pyx_v_dzdx = (((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_5 * __pyx_v_indata.strides[0]) ) + __pyx_t_6 * __pyx_v_indata.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_7 * __pyx_v_indata.strides[0]) ) + __pyx_t_8 * __pyx_v_indata.strides[1]) )))) / 2.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">13</span>: <span class=\"n\">dzdy</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">2</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">])</span> <span class=\"o\">/</span> <span class=\"mf\">2</span></pre>\n<pre class='cython code score-0 '> __pyx_t_9 = __pyx_v_i;\n __pyx_t_10 = (__pyx_v_j + 1);\n if (__pyx_t_9 &lt; 0) __pyx_t_9 += __pyx_v_indata.shape[0];\n if (__pyx_t_10 &lt; 0) __pyx_t_10 += __pyx_v_indata.shape[1];\n __pyx_t_11 = (__pyx_v_i + 2);\n __pyx_t_12 = (__pyx_v_j + 1);\n if (__pyx_t_11 &lt; 0) __pyx_t_11 += __pyx_v_indata.shape[0];\n if (__pyx_t_12 &lt; 0) __pyx_t_12 += __pyx_v_indata.shape[1];\n __pyx_v_dzdy = (((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_9 * __pyx_v_indata.strides[0]) ) + __pyx_t_10 * __pyx_v_indata.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_11 * __pyx_v_indata.strides[0]) ) + __pyx_t_12 * __pyx_v_indata.strides[1]) )))) / 2.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">14</span>: <span class=\"n\">k</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">dzdx</span> <span class=\"o\">*</span> <span class=\"n\">dzdx</span><span class=\"p\">)</span> <span class=\"o\">+</span> <span class=\"p\">(</span><span class=\"n\">dzdy</span> <span class=\"o\">*</span> <span class=\"n\">dzdy</span><span class=\"p\">)</span></pre>\n<pre class='cython code score-0 '> __pyx_v_k = ((__pyx_v_dzdx * __pyx_v_dzdx) + (__pyx_v_dzdy * __pyx_v_dzdy));\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">15</span>: <span class=\"n\">slp</span> <span class=\"o\">=</span> <span class=\"n\">k</span> <span class=\"o\">**</span> <span class=\"mf\">0.5</span> <span class=\"o\">*</span> <span class=\"mf\">100</span></pre>\n<pre class='cython code score-0 '> __pyx_v_slp = (pow(__pyx_v_k, 0.5) * 100.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">16</span>: <span class=\"n\">outdata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"n\">slp</span></pre>\n<pre class='cython code score-0 '> __pyx_t_13 = __pyx_v_i;\n __pyx_t_14 = __pyx_v_j;\n if (__pyx_t_13 &lt; 0) __pyx_t_13 += __pyx_v_outdata.shape[0];\n if (__pyx_t_14 &lt; 0) __pyx_t_14 += __pyx_v_outdata.shape[1];\n *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_outdata.data + __pyx_t_13 * __pyx_v_outdata.strides[0]) ) + __pyx_t_14 * __pyx_v_outdata.strides[1]) )) = __pyx_v_slp;\n }\n }\n</pre></div></body></html>",
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"metadata": {},
"execution_count": 5
}
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"metadata": {
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"cell_type": "code",
"source": "reset_outdata()\n%timeit slope_cython_pow(indata, outdata)",
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"text": "10 loops, best of 3: 177 ms per loop\n",
"name": "stdout"
}
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"source": "%%cython -a\nimport cython\nfrom libc.math cimport sqrt\n\[email protected](False)\ndef slope_cython_libc_sqrt(double [:, :] indata, double [:, :] outdata):\n cdef int I, J\n cdef int i, j, x\n cdef double k, slp, dzdx, dzdy\n I = outdata.shape[0]\n J = outdata.shape[1]\n for i in range(I):\n for j in range(J):\n dzdx = (indata[i+1, j] - indata[i+1, j+2]) / 2\n dzdy = (indata[i, j+1] - indata[i+2, j+1]) / 2\n k = (dzdx * dzdx) + (dzdy * dzdy)\n # A simple switch to using libc sqrt goes a long way!\n slp = sqrt(k) * 100\n outdata[i, j] = slp",
"execution_count": 7,
"outputs": [
{
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__pyx_n_s_cython_magic_046cf4098acedac426);<span class='error_goto'> if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_t_1);\n if (<span class='py_c_api'>PyDict_SetItem</span>(__pyx_d, __pyx_n_s_slope_cython_libc_sqrt, __pyx_t_1) &lt; 0) <span class='error_goto'>{__pyx_filename = __pyx_f[0]; __pyx_lineno = 5; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='pyx_macro_api'>__Pyx_DECREF</span>(__pyx_t_1); __pyx_t_1 = 0;\n __pyx_codeobj__15 = (PyObject*)<span class='pyx_c_api'>__Pyx_PyCode_New</span>(2, 0, 11, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__14, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_pts08_cache_ipython_cython, __pyx_n_s_slope_cython_libc_sqrt, 5, __pyx_empty_bytes);<span class='error_goto'> if (unlikely(!__pyx_codeobj__15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 5; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">06</span>: <span class=\"k\">cdef</span> <span class=\"kt\">int</span> <span class=\"nf\">I</span><span class=\"p\">,</span> <span class=\"nf\">J</span></pre>\n<pre class=\"cython line score-0\">&#xA0;<span class=\"\">07</span>: <span class=\"k\">cdef</span> <span class=\"kt\">int</span> <span class=\"nf\">i</span><span class=\"p\">,</span> <span class=\"nf\">j</span><span class=\"p\">,</span> <span class=\"nf\">x</span></pre>\n<pre class=\"cython line score-0\">&#xA0;<span class=\"\">08</span>: <span class=\"k\">cdef</span> <span class=\"kt\">double</span> <span class=\"nf\">k</span><span class=\"p\">,</span> <span class=\"nf\">slp</span><span class=\"p\">,</span> <span class=\"nf\">dzdx</span><span class=\"p\">,</span> <span class=\"nf\">dzdy</span></pre>\n<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">09</span>: <span class=\"n\">I</span> <span class=\"o\">=</span> <span class=\"n\">outdata</span><span class=\"o\">.</span><span class=\"n\">shape</span><span class=\"p\">[</span><span class=\"mf\">0</span><span class=\"p\">]</span></pre>\n<pre class='cython code score-0 '> __pyx_v_I = (__pyx_v_outdata.shape[0]);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">10</span>: <span class=\"n\">J</span> <span class=\"o\">=</span> <span class=\"n\">outdata</span><span class=\"o\">.</span><span class=\"n\">shape</span><span class=\"p\">[</span><span class=\"mf\">1</span><span class=\"p\">]</span></pre>\n<pre class='cython code score-0 '> __pyx_v_J = (__pyx_v_outdata.shape[1]);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">11</span>: <span class=\"k\">for</span> <span class=\"n\">i</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"n\">I</span><span class=\"p\">):</span></pre>\n<pre class='cython code score-0 '> __pyx_t_1 = __pyx_v_I;\n for (__pyx_t_2 = 0; __pyx_t_2 &lt; __pyx_t_1; __pyx_t_2+=1) {\n __pyx_v_i = __pyx_t_2;\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">12</span>: <span class=\"k\">for</span> <span class=\"n\">j</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"n\">J</span><span class=\"p\">):</span></pre>\n<pre class='cython code score-0 '> __pyx_t_3 = __pyx_v_J;\n for (__pyx_t_4 = 0; __pyx_t_4 &lt; __pyx_t_3; __pyx_t_4+=1) {\n __pyx_v_j = __pyx_t_4;\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">13</span>: <span class=\"n\">dzdx</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">2</span><span class=\"p\">])</span> <span class=\"o\">/</span> <span class=\"mf\">2</span></pre>\n<pre class='cython code score-0 '> __pyx_t_5 = (__pyx_v_i + 1);\n __pyx_t_6 = __pyx_v_j;\n if (__pyx_t_5 &lt; 0) __pyx_t_5 += __pyx_v_indata.shape[0];\n if (__pyx_t_6 &lt; 0) __pyx_t_6 += __pyx_v_indata.shape[1];\n __pyx_t_7 = (__pyx_v_i + 1);\n __pyx_t_8 = (__pyx_v_j + 2);\n if (__pyx_t_7 &lt; 0) __pyx_t_7 += __pyx_v_indata.shape[0];\n if (__pyx_t_8 &lt; 0) __pyx_t_8 += __pyx_v_indata.shape[1];\n __pyx_v_dzdx = (((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_5 * __pyx_v_indata.strides[0]) ) + __pyx_t_6 * __pyx_v_indata.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_7 * __pyx_v_indata.strides[0]) ) + __pyx_t_8 * __pyx_v_indata.strides[1]) )))) / 2.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">14</span>: <span class=\"n\">dzdy</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">2</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">])</span> <span class=\"o\">/</span> <span class=\"mf\">2</span></pre>\n<pre class='cython code score-0 '> __pyx_t_9 = __pyx_v_i;\n __pyx_t_10 = (__pyx_v_j + 1);\n if (__pyx_t_9 &lt; 0) __pyx_t_9 += __pyx_v_indata.shape[0];\n if (__pyx_t_10 &lt; 0) __pyx_t_10 += __pyx_v_indata.shape[1];\n __pyx_t_11 = (__pyx_v_i + 2);\n __pyx_t_12 = (__pyx_v_j + 1);\n if (__pyx_t_11 &lt; 0) __pyx_t_11 += __pyx_v_indata.shape[0];\n if (__pyx_t_12 &lt; 0) __pyx_t_12 += __pyx_v_indata.shape[1];\n __pyx_v_dzdy = (((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_9 * __pyx_v_indata.strides[0]) ) + __pyx_t_10 * __pyx_v_indata.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_11 * __pyx_v_indata.strides[0]) ) + __pyx_t_12 * __pyx_v_indata.strides[1]) )))) / 2.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">15</span>: <span class=\"n\">k</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">dzdx</span> <span class=\"o\">*</span> <span class=\"n\">dzdx</span><span class=\"p\">)</span> <span class=\"o\">+</span> <span class=\"p\">(</span><span class=\"n\">dzdy</span> <span class=\"o\">*</span> <span class=\"n\">dzdy</span><span class=\"p\">)</span></pre>\n<pre class='cython code score-0 '> __pyx_v_k = ((__pyx_v_dzdx * __pyx_v_dzdx) + (__pyx_v_dzdy * __pyx_v_dzdy));\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">16</span>: <span class=\"n\">slp</span> <span class=\"o\">=</span> <span class=\"n\">sqrt</span><span class=\"p\">(</span><span class=\"n\">k</span><span class=\"p\">)</span> <span class=\"o\">*</span> <span class=\"mf\">100</span></pre>\n<pre class='cython code score-0 '> __pyx_v_slp = (sqrt(__pyx_v_k) * 100.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">17</span>: <span class=\"n\">outdata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"n\">slp</span></pre>\n<pre class='cython code score-0 '> __pyx_t_13 = __pyx_v_i;\n __pyx_t_14 = __pyx_v_j;\n if (__pyx_t_13 &lt; 0) __pyx_t_13 += __pyx_v_outdata.shape[0];\n if (__pyx_t_14 &lt; 0) __pyx_t_14 += __pyx_v_outdata.shape[1];\n *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_outdata.data + __pyx_t_13 * __pyx_v_outdata.strides[0]) ) + __pyx_t_14 * __pyx_v_outdata.strides[1]) )) = __pyx_v_slp;\n }\n }\n</pre></div></body></html>",
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"metadata": {},
"execution_count": 7
}
]
},
{
"metadata": {
"trusted": true,
"collapsed": false
},
"cell_type": "code",
"source": "reset_outdata()\n%timeit slope_cython_libc_sqrt(indata, outdata)",
"execution_count": 8,
"outputs": [
{
"output_type": "stream",
"text": "100 loops, best of 3: 16.5 ms per loop\n",
"name": "stdout"
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"trusted": true
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"cell_type": "code",
"source": "%%cython --compile-args=-fopenmp --link-args=-fopenmp --force -a\n\nimport cython\nfrom cython.parallel import prange, parallel\n\n\[email protected](False)\ndef slope_cython_openmp_pow(double [:, :] indata, double [:, :] outdata):\n cdef int I, J\n cdef int i, j, x\n cdef double k, slp, dzdx, dzdy\n I = outdata.shape[0]\n J = outdata.shape[1]\n with nogil, parallel(num_threads=4):\n for i in prange(I, schedule='dynamic'):\n for j in range(J):\n dzdx = (indata[i+1, j] - indata[i+1, j+2]) / 2\n dzdy = (indata[i, j+1] - indata[i+2, j+1]) / 2\n k = (dzdx * dzdx) + (dzdy * dzdy)\n slp = k ** 0.5 * 100\n outdata[i, j] = slp",
"execution_count": 9,
"outputs": [
{
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};\n __Pyx_memviewslice __pyx_v_outdata = { 0, 0, { 0 }, { 0 }, { 0 } };\n PyObject *__pyx_r = 0;\n <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"slope_cython_openmp_pow (wrapper)\", 0);\n {\n static PyObject **__pyx_pyargnames[] = {&amp;__pyx_n_s_indata,&amp;__pyx_n_s_outdata,0};\n PyObject* values[2] = {0,0};\n if (unlikely(__pyx_kwds)) {\n Py_ssize_t kw_args;\n const Py_ssize_t pos_args = <span class='py_macro_api'>PyTuple_GET_SIZE</span>(__pyx_args);\n switch (pos_args) {\n case 2: values[1] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 1);\n case 1: values[0] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 0);\n case 0: break;\n default: goto __pyx_L5_argtuple_error;\n }\n kw_args = <span class='py_c_api'>PyDict_Size</span>(__pyx_kwds);\n switch (pos_args) {\n case 0:\n if (likely((values[0] = <span class='py_c_api'>PyDict_GetItem</span>(__pyx_kwds, __pyx_n_s_indata)) != 0)) kw_args--;\n else goto __pyx_L5_argtuple_error;\n case 1:\n if (likely((values[1] = <span class='py_c_api'>PyDict_GetItem</span>(__pyx_kwds, __pyx_n_s_outdata)) != 0)) kw_args--;\n else {\n <span class='pyx_c_api'>__Pyx_RaiseArgtupleInvalid</span>(\"slope_cython_openmp_pow\", 1, 2, 2, 1); <span class='error_goto'>{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;}</span>\n }\n }\n if (unlikely(kw_args &gt; 0)) {\n if (unlikely(<span class='pyx_c_api'>__Pyx_ParseOptionalKeywords</span>(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, \"slope_cython_openmp_pow\") &lt; 0)) <span class='error_goto'>{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;}</span>\n }\n } else if (<span class='py_macro_api'>PyTuple_GET_SIZE</span>(__pyx_args) != 2) {\n goto __pyx_L5_argtuple_error;\n } else {\n values[0] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 0);\n values[1] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 1);\n }\n __pyx_v_indata = <span class='pyx_c_api'>__Pyx_PyObject_to_MemoryviewSlice_dsds_double</span>(values[0]);<span class='error_goto'> if (unlikely(!__pyx_v_indata.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;}</span>\n __pyx_v_outdata = <span class='pyx_c_api'>__Pyx_PyObject_to_MemoryviewSlice_dsds_double</span>(values[1]);<span class='error_goto'> if (unlikely(!__pyx_v_outdata.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;}</span>\n }\n goto __pyx_L4_argument_unpacking_done;\n __pyx_L5_argtuple_error:;\n <span class='pyx_c_api'>__Pyx_RaiseArgtupleInvalid</span>(\"slope_cython_openmp_pow\", 1, 2, 2, <span class='py_macro_api'>PyTuple_GET_SIZE</span>(__pyx_args)); <span class='error_goto'>{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;}</span>\n __pyx_L3_error:;\n <span class='pyx_c_api'>__Pyx_AddTraceback</span>(\"_cython_magic_2f77b1cc5912c2e29f373fd669b4b05f.slope_cython_openmp_pow\", __pyx_clineno, __pyx_lineno, __pyx_filename);\n <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n return NULL;\n __pyx_L4_argument_unpacking_done:;\n __pyx_r = __pyx_pf_46_cython_magic_2f77b1cc5912c2e29f373fd669b4b05f_slope_cython_openmp_pow(__pyx_self, __pyx_v_indata, __pyx_v_outdata);\n int __pyx_lineno = 0;\n const char *__pyx_filename = NULL;\n int __pyx_clineno = 0;\n\n /* function exit code */\n <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n return __pyx_r;\n}\n\nstatic PyObject *__pyx_pf_46_cython_magic_2f77b1cc5912c2e29f373fd669b4b05f_slope_cython_openmp_pow(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_indata, __Pyx_memviewslice __pyx_v_outdata) {\n CYTHON_UNUSED int __pyx_v_I;\n int __pyx_v_J;\n int __pyx_v_i;\n int __pyx_v_j;\n double __pyx_v_k;\n double __pyx_v_slp;\n double __pyx_v_dzdx;\n double __pyx_v_dzdy;\n PyObject *__pyx_r = NULL;\n <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"slope_cython_openmp_pow\", 0);\n/* … */\n /* function exit code */\n __pyx_r = Py_None; <span class='pyx_macro_api'>__Pyx_INCREF</span>(Py_None);\n __PYX_XDEC_MEMVIEW(&amp;__pyx_v_indata, 1);\n __PYX_XDEC_MEMVIEW(&amp;__pyx_v_outdata, 1);\n <span class='refnanny'>__Pyx_XGIVEREF</span>(__pyx_r);\n <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n return __pyx_r;\n}\n/* … */\n __pyx_tuple__14 = <span class='py_c_api'>PyTuple_Pack</span>(11, __pyx_n_s_indata, __pyx_n_s_outdata, __pyx_n_s_I, __pyx_n_s_J, __pyx_n_s_i, __pyx_n_s_j, __pyx_n_s_x, __pyx_n_s_k, __pyx_n_s_slp, __pyx_n_s_dzdx, __pyx_n_s_dzdy);<span class='error_goto'> if (unlikely(!__pyx_tuple__14)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_tuple__14);\n <span class='refnanny'>__Pyx_GIVEREF</span>(__pyx_tuple__14);\n/* … */\n __pyx_t_1 = PyCFunction_NewEx(&amp;__pyx_mdef_46_cython_magic_2f77b1cc5912c2e29f373fd669b4b05f_1slope_cython_openmp_pow, NULL, __pyx_n_s_cython_magic_2f77b1cc5912c2e29f);<span class='error_goto'> if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_t_1);\n if (<span class='py_c_api'>PyDict_SetItem</span>(__pyx_d, __pyx_n_s_slope_cython_openmp_pow, __pyx_t_1) &lt; 0) <span class='error_goto'>{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='pyx_macro_api'>__Pyx_DECREF</span>(__pyx_t_1); __pyx_t_1 = 0;\n __pyx_codeobj__15 = (PyObject*)<span class='pyx_c_api'>__Pyx_PyCode_New</span>(2, 0, 11, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__14, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_pts08_cache_ipython_cython, __pyx_n_s_slope_cython_openmp_pow, 7, __pyx_empty_bytes);<span class='error_goto'> if (unlikely(!__pyx_codeobj__15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">08</span>: <span class=\"k\">cdef</span> <span class=\"kt\">int</span> <span class=\"nf\">I</span><span class=\"p\">,</span> <span class=\"nf\">J</span></pre>\n<pre class=\"cython line score-0\">&#xA0;<span class=\"\">09</span>: <span class=\"k\">cdef</span> <span class=\"kt\">int</span> <span class=\"nf\">i</span><span class=\"p\">,</span> <span class=\"nf\">j</span><span class=\"p\">,</span> <span class=\"nf\">x</span></pre>\n<pre class=\"cython line score-0\">&#xA0;<span class=\"\">10</span>: <span class=\"k\">cdef</span> <span class=\"kt\">double</span> <span class=\"nf\">k</span><span class=\"p\">,</span> <span class=\"nf\">slp</span><span class=\"p\">,</span> <span class=\"nf\">dzdx</span><span class=\"p\">,</span> <span class=\"nf\">dzdy</span></pre>\n<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">11</span>: <span class=\"n\">I</span> <span class=\"o\">=</span> <span class=\"n\">outdata</span><span class=\"o\">.</span><span class=\"n\">shape</span><span class=\"p\">[</span><span class=\"mf\">0</span><span class=\"p\">]</span></pre>\n<pre class='cython code score-0 '> __pyx_v_I = (__pyx_v_outdata.shape[0]);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">12</span>: <span class=\"n\">J</span> <span class=\"o\">=</span> <span class=\"n\">outdata</span><span class=\"o\">.</span><span class=\"n\">shape</span><span class=\"p\">[</span><span class=\"mf\">1</span><span class=\"p\">]</span></pre>\n<pre class='cython code score-0 '> __pyx_v_J = (__pyx_v_outdata.shape[1]);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">13</span>: <span class=\"k\">with</span> <span class=\"k\">nogil</span><span class=\"p\">,</span> <span class=\"n\">parallel</span><span class=\"p\">(</span><span class=\"n\">num_threads</span><span class=\"o\">=</span><span class=\"mf\">4</span><span class=\"p\">):</span></pre>\n<pre class='cython code score-0 '> {\n #ifdef WITH_THREAD\n PyThreadState *_save;\n Py_UNBLOCK_THREADS\n #endif\n /*try:*/ {\n {\n #if ((defined(__APPLE__) || defined(__OSX__)) &amp;&amp; (defined(__GNUC__) &amp;&amp; (__GNUC__ &gt; 2 || (__GNUC__ == 2 &amp;&amp; (__GNUC_MINOR__ &gt; 95)))))\n #undef likely\n #undef unlikely\n #define likely(x) (x)\n #define unlikely(x) (x)\n #endif\n #ifdef _OPENMP\n #pragma omp parallel num_threads(4)\n #endif /* _OPENMP */\n {\n/* … */\n /*finally:*/ {\n /*normal exit:*/{\n #ifdef WITH_THREAD\n Py_BLOCK_THREADS\n #endif\n goto __pyx_L5;\n }\n __pyx_L5:;\n }\n }\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">14</span>: <span class=\"k\">for</span> <span class=\"n\">i</span> <span class=\"ow\">in</span> <span class=\"n\">prange</span><span class=\"p\">(</span><span class=\"n\">I</span><span class=\"p\">,</span> <span class=\"n\">schedule</span><span class=\"o\">=</span><span class=\"s\">&#39;dynamic&#39;</span><span class=\"p\">):</span></pre>\n<pre class='cython code score-0 '> __pyx_t_1 = __pyx_v_I;\n if (1 == 0) abort();\n {\n __pyx_t_3 = (__pyx_t_1 - 0) / 1;\n if (__pyx_t_3 &gt; 0)\n {\n #ifdef _OPENMP\n #pragma omp for lastprivate(__pyx_v_slp) lastprivate(__pyx_v_dzdy) lastprivate(__pyx_v_k) lastprivate(__pyx_v_dzdx) lastprivate(__pyx_v_j) firstprivate(__pyx_v_i) lastprivate(__pyx_v_i) schedule(dynamic)\n #endif /* _OPENMP */\n for (__pyx_t_2 = 0; __pyx_t_2 &lt; __pyx_t_3; __pyx_t_2++){\n {\n __pyx_v_i = 0 + 1 * __pyx_t_2;\n /* Initialize private variables to invalid values */\n __pyx_v_slp = ((double)__PYX_NAN());\n __pyx_v_dzdy = ((double)__PYX_NAN());\n __pyx_v_k = ((double)__PYX_NAN());\n __pyx_v_dzdx = ((double)__PYX_NAN());\n __pyx_v_j = ((int)0xbad0bad0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">15</span>: <span class=\"k\">for</span> <span class=\"n\">j</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"n\">J</span><span class=\"p\">):</span></pre>\n<pre class='cython code score-0 '> __pyx_t_4 = __pyx_v_J;\n for (__pyx_t_5 = 0; __pyx_t_5 &lt; __pyx_t_4; __pyx_t_5+=1) {\n __pyx_v_j = __pyx_t_5;\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">16</span>: <span class=\"n\">dzdx</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">2</span><span class=\"p\">])</span> <span class=\"o\">/</span> <span class=\"mf\">2</span></pre>\n<pre class='cython code score-0 '> __pyx_t_6 = (__pyx_v_i + 1);\n __pyx_t_7 = __pyx_v_j;\n if (__pyx_t_6 &lt; 0) __pyx_t_6 += __pyx_v_indata.shape[0];\n if (__pyx_t_7 &lt; 0) __pyx_t_7 += __pyx_v_indata.shape[1];\n __pyx_t_8 = (__pyx_v_i + 1);\n __pyx_t_9 = (__pyx_v_j + 2);\n if (__pyx_t_8 &lt; 0) __pyx_t_8 += __pyx_v_indata.shape[0];\n if (__pyx_t_9 &lt; 0) __pyx_t_9 += __pyx_v_indata.shape[1];\n __pyx_v_dzdx = (((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_6 * __pyx_v_indata.strides[0]) ) + __pyx_t_7 * __pyx_v_indata.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_8 * __pyx_v_indata.strides[0]) ) + __pyx_t_9 * __pyx_v_indata.strides[1]) )))) / 2.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">17</span>: <span class=\"n\">dzdy</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">2</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">])</span> <span class=\"o\">/</span> <span class=\"mf\">2</span></pre>\n<pre class='cython code score-0 '> __pyx_t_10 = __pyx_v_i;\n __pyx_t_11 = (__pyx_v_j + 1);\n if (__pyx_t_10 &lt; 0) __pyx_t_10 += __pyx_v_indata.shape[0];\n if (__pyx_t_11 &lt; 0) __pyx_t_11 += __pyx_v_indata.shape[1];\n __pyx_t_12 = (__pyx_v_i + 2);\n __pyx_t_13 = (__pyx_v_j + 1);\n if (__pyx_t_12 &lt; 0) __pyx_t_12 += __pyx_v_indata.shape[0];\n if (__pyx_t_13 &lt; 0) __pyx_t_13 += __pyx_v_indata.shape[1];\n __pyx_v_dzdy = (((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_10 * __pyx_v_indata.strides[0]) ) + __pyx_t_11 * __pyx_v_indata.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_12 * __pyx_v_indata.strides[0]) ) + __pyx_t_13 * __pyx_v_indata.strides[1]) )))) / 2.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">18</span>: <span class=\"n\">k</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">dzdx</span> <span class=\"o\">*</span> <span class=\"n\">dzdx</span><span class=\"p\">)</span> <span class=\"o\">+</span> <span class=\"p\">(</span><span class=\"n\">dzdy</span> <span class=\"o\">*</span> <span class=\"n\">dzdy</span><span class=\"p\">)</span></pre>\n<pre class='cython code score-0 '> __pyx_v_k = ((__pyx_v_dzdx * __pyx_v_dzdx) + (__pyx_v_dzdy * __pyx_v_dzdy));\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">19</span>: <span class=\"n\">slp</span> <span class=\"o\">=</span> <span class=\"n\">k</span> <span class=\"o\">**</span> <span class=\"mf\">0.5</span> <span class=\"o\">*</span> <span class=\"mf\">100</span></pre>\n<pre class='cython code score-0 '> __pyx_v_slp = (pow(__pyx_v_k, 0.5) * 100.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">20</span>: <span class=\"n\">outdata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"n\">slp</span></pre>\n<pre class='cython code score-0 '> __pyx_t_14 = __pyx_v_i;\n __pyx_t_15 = __pyx_v_j;\n if (__pyx_t_14 &lt; 0) __pyx_t_14 += __pyx_v_outdata.shape[0];\n if (__pyx_t_15 &lt; 0) __pyx_t_15 += __pyx_v_outdata.shape[1];\n *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_outdata.data + __pyx_t_14 * __pyx_v_outdata.strides[0]) ) + __pyx_t_15 * __pyx_v_outdata.strides[1]) )) = __pyx_v_slp;\n }\n }\n }\n }\n }\n }\n }\n #if ((defined(__APPLE__) || defined(__OSX__)) &amp;&amp; (defined(__GNUC__) &amp;&amp; (__GNUC__ &gt; 2 || (__GNUC__ == 2 &amp;&amp; (__GNUC_MINOR__ &gt; 95)))))\n #undef likely\n #undef unlikely\n #define likely(x) __builtin_expect(!!(x), 1)\n #define unlikely(x) __builtin_expect(!!(x), 0)\n #endif\n }\n</pre></div></body></html>",
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"metadata": {},
"execution_count": 9
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "reset_outdata()\n%timeit slope_cython_openmp_pow(indata, outdata)",
"execution_count": 10,
"outputs": [
{
"output_type": "stream",
"text": "10 loops, best of 3: 42.3 ms per loop\n",
"name": "stdout"
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "%%cython --compile-args=-fopenmp --link-args=-fopenmp --force -a\n\nimport cython\nfrom cython.parallel import prange, parallel\nfrom libc.math cimport sqrt\n\[email protected](False)\ndef slope_cython_openmp_sqrt(double [:, :] indata, double [:, :] outdata):\n cdef int I, J\n cdef int i, j, x\n cdef double k, slp, dzdx, dzdy\n I = outdata.shape[0]\n J = outdata.shape[1]\n with nogil, parallel(num_threads=4):\n for i in prange(I, schedule='dynamic'):\n for j in range(J):\n dzdx = (indata[i+1, j] - indata[i+1, j+2]) / 2\n dzdy = (indata[i, j+1] - indata[i+2, j+1]) / 2\n k = (dzdx * dzdx) + (dzdy * dzdy)\n # A simple switch to using libc sqrt goes a long way!\n slp = sqrt(k) * 100\n outdata[i, j] = slp",
"execution_count": 11,
"outputs": [
{
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*__pyx_pw_46_cython_magic_7033f39a16f09219f322812ae408dac1_1slope_cython_openmp_sqrt(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {\n __Pyx_memviewslice __pyx_v_indata = { 0, 0, { 0 }, { 0 }, { 0 } };\n __Pyx_memviewslice __pyx_v_outdata = { 0, 0, { 0 }, { 0 }, { 0 } };\n PyObject *__pyx_r = 0;\n <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"slope_cython_openmp_sqrt (wrapper)\", 0);\n {\n static PyObject **__pyx_pyargnames[] = {&amp;__pyx_n_s_indata,&amp;__pyx_n_s_outdata,0};\n PyObject* values[2] = {0,0};\n if (unlikely(__pyx_kwds)) {\n Py_ssize_t kw_args;\n const Py_ssize_t pos_args = <span class='py_macro_api'>PyTuple_GET_SIZE</span>(__pyx_args);\n switch (pos_args) {\n case 2: values[1] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 1);\n case 1: values[0] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 0);\n case 0: break;\n default: goto __pyx_L5_argtuple_error;\n }\n kw_args = <span class='py_c_api'>PyDict_Size</span>(__pyx_kwds);\n switch (pos_args) {\n case 0:\n if (likely((values[0] = <span class='py_c_api'>PyDict_GetItem</span>(__pyx_kwds, __pyx_n_s_indata)) != 0)) kw_args--;\n else goto __pyx_L5_argtuple_error;\n case 1:\n if (likely((values[1] = <span class='py_c_api'>PyDict_GetItem</span>(__pyx_kwds, __pyx_n_s_outdata)) != 0)) kw_args--;\n else {\n <span class='pyx_c_api'>__Pyx_RaiseArgtupleInvalid</span>(\"slope_cython_openmp_sqrt\", 1, 2, 2, 1); <span class='error_goto'>{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;}</span>\n }\n }\n if (unlikely(kw_args &gt; 0)) {\n if (unlikely(<span class='pyx_c_api'>__Pyx_ParseOptionalKeywords</span>(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, \"slope_cython_openmp_sqrt\") &lt; 0)) <span class='error_goto'>{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;}</span>\n }\n } else if (<span class='py_macro_api'>PyTuple_GET_SIZE</span>(__pyx_args) != 2) {\n goto __pyx_L5_argtuple_error;\n } else {\n values[0] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 0);\n values[1] = <span class='py_macro_api'>PyTuple_GET_ITEM</span>(__pyx_args, 1);\n }\n __pyx_v_indata = <span class='pyx_c_api'>__Pyx_PyObject_to_MemoryviewSlice_dsds_double</span>(values[0]);<span class='error_goto'> if (unlikely(!__pyx_v_indata.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;}</span>\n __pyx_v_outdata = <span class='pyx_c_api'>__Pyx_PyObject_to_MemoryviewSlice_dsds_double</span>(values[1]);<span class='error_goto'> if (unlikely(!__pyx_v_outdata.memview)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;}</span>\n }\n goto __pyx_L4_argument_unpacking_done;\n __pyx_L5_argtuple_error:;\n <span class='pyx_c_api'>__Pyx_RaiseArgtupleInvalid</span>(\"slope_cython_openmp_sqrt\", 1, 2, 2, <span class='py_macro_api'>PyTuple_GET_SIZE</span>(__pyx_args)); <span class='error_goto'>{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L3_error;}</span>\n __pyx_L3_error:;\n <span class='pyx_c_api'>__Pyx_AddTraceback</span>(\"_cython_magic_7033f39a16f09219f322812ae408dac1.slope_cython_openmp_sqrt\", __pyx_clineno, __pyx_lineno, __pyx_filename);\n <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n return NULL;\n __pyx_L4_argument_unpacking_done:;\n __pyx_r = __pyx_pf_46_cython_magic_7033f39a16f09219f322812ae408dac1_slope_cython_openmp_sqrt(__pyx_self, __pyx_v_indata, __pyx_v_outdata);\n int __pyx_lineno = 0;\n const char *__pyx_filename = NULL;\n int __pyx_clineno = 0;\n\n /* function exit code */\n <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n return __pyx_r;\n}\n\nstatic PyObject *__pyx_pf_46_cython_magic_7033f39a16f09219f322812ae408dac1_slope_cython_openmp_sqrt(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_indata, __Pyx_memviewslice __pyx_v_outdata) {\n CYTHON_UNUSED int __pyx_v_I;\n int __pyx_v_J;\n int __pyx_v_i;\n int __pyx_v_j;\n double __pyx_v_k;\n double __pyx_v_slp;\n double __pyx_v_dzdx;\n double __pyx_v_dzdy;\n PyObject *__pyx_r = NULL;\n <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"slope_cython_openmp_sqrt\", 0);\n/* … */\n /* function exit code */\n __pyx_r = Py_None; <span class='pyx_macro_api'>__Pyx_INCREF</span>(Py_None);\n __PYX_XDEC_MEMVIEW(&amp;__pyx_v_indata, 1);\n __PYX_XDEC_MEMVIEW(&amp;__pyx_v_outdata, 1);\n <span class='refnanny'>__Pyx_XGIVEREF</span>(__pyx_r);\n <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n return __pyx_r;\n}\n/* … */\n __pyx_tuple__14 = <span class='py_c_api'>PyTuple_Pack</span>(11, __pyx_n_s_indata, __pyx_n_s_outdata, __pyx_n_s_I, __pyx_n_s_J, __pyx_n_s_i, __pyx_n_s_j, __pyx_n_s_x, __pyx_n_s_k, __pyx_n_s_slp, __pyx_n_s_dzdx, __pyx_n_s_dzdy);<span class='error_goto'> if (unlikely(!__pyx_tuple__14)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_tuple__14);\n <span class='refnanny'>__Pyx_GIVEREF</span>(__pyx_tuple__14);\n/* … */\n __pyx_t_1 = PyCFunction_NewEx(&amp;__pyx_mdef_46_cython_magic_7033f39a16f09219f322812ae408dac1_1slope_cython_openmp_sqrt, NULL, __pyx_n_s_cython_magic_7033f39a16f09219f3);<span class='error_goto'> if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_t_1);\n if (<span class='py_c_api'>PyDict_SetItem</span>(__pyx_d, __pyx_n_s_slope_cython_openmp_sqrt, __pyx_t_1) &lt; 0) <span class='error_goto'>{__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n <span class='pyx_macro_api'>__Pyx_DECREF</span>(__pyx_t_1); __pyx_t_1 = 0;\n __pyx_codeobj__15 = (PyObject*)<span class='pyx_c_api'>__Pyx_PyCode_New</span>(2, 0, 11, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__14, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_home_pts08_cache_ipython_cython, __pyx_n_s_slope_cython_openmp_sqrt, 7, __pyx_empty_bytes);<span class='error_goto'> if (unlikely(!__pyx_codeobj__15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;}</span>\n</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">08</span>: <span class=\"k\">cdef</span> <span class=\"kt\">int</span> <span class=\"nf\">I</span><span class=\"p\">,</span> <span class=\"nf\">J</span></pre>\n<pre class=\"cython line score-0\">&#xA0;<span class=\"\">09</span>: <span class=\"k\">cdef</span> <span class=\"kt\">int</span> <span class=\"nf\">i</span><span class=\"p\">,</span> <span class=\"nf\">j</span><span class=\"p\">,</span> <span class=\"nf\">x</span></pre>\n<pre class=\"cython line score-0\">&#xA0;<span class=\"\">10</span>: <span class=\"k\">cdef</span> <span class=\"kt\">double</span> <span class=\"nf\">k</span><span class=\"p\">,</span> <span class=\"nf\">slp</span><span class=\"p\">,</span> <span class=\"nf\">dzdx</span><span class=\"p\">,</span> <span class=\"nf\">dzdy</span></pre>\n<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">11</span>: <span class=\"n\">I</span> <span class=\"o\">=</span> <span class=\"n\">outdata</span><span class=\"o\">.</span><span class=\"n\">shape</span><span class=\"p\">[</span><span class=\"mf\">0</span><span class=\"p\">]</span></pre>\n<pre class='cython code score-0 '> __pyx_v_I = (__pyx_v_outdata.shape[0]);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">12</span>: <span class=\"n\">J</span> <span class=\"o\">=</span> <span class=\"n\">outdata</span><span class=\"o\">.</span><span class=\"n\">shape</span><span class=\"p\">[</span><span class=\"mf\">1</span><span class=\"p\">]</span></pre>\n<pre class='cython code score-0 '> __pyx_v_J = (__pyx_v_outdata.shape[1]);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">13</span>: <span class=\"k\">with</span> <span class=\"k\">nogil</span><span class=\"p\">,</span> <span class=\"n\">parallel</span><span class=\"p\">(</span><span class=\"n\">num_threads</span><span class=\"o\">=</span><span class=\"mf\">4</span><span class=\"p\">):</span></pre>\n<pre class='cython code score-0 '> {\n #ifdef WITH_THREAD\n PyThreadState *_save;\n Py_UNBLOCK_THREADS\n #endif\n /*try:*/ {\n {\n #if ((defined(__APPLE__) || defined(__OSX__)) &amp;&amp; (defined(__GNUC__) &amp;&amp; (__GNUC__ &gt; 2 || (__GNUC__ == 2 &amp;&amp; (__GNUC_MINOR__ &gt; 95)))))\n #undef likely\n #undef unlikely\n #define likely(x) (x)\n #define unlikely(x) (x)\n #endif\n #ifdef _OPENMP\n #pragma omp parallel num_threads(4)\n #endif /* _OPENMP */\n {\n/* … */\n /*finally:*/ {\n /*normal exit:*/{\n #ifdef WITH_THREAD\n Py_BLOCK_THREADS\n #endif\n goto __pyx_L5;\n }\n __pyx_L5:;\n }\n }\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">14</span>: <span class=\"k\">for</span> <span class=\"n\">i</span> <span class=\"ow\">in</span> <span class=\"n\">prange</span><span class=\"p\">(</span><span class=\"n\">I</span><span class=\"p\">,</span> <span class=\"n\">schedule</span><span class=\"o\">=</span><span class=\"s\">&#39;dynamic&#39;</span><span class=\"p\">):</span></pre>\n<pre class='cython code score-0 '> __pyx_t_1 = __pyx_v_I;\n if (1 == 0) abort();\n {\n __pyx_t_3 = (__pyx_t_1 - 0) / 1;\n if (__pyx_t_3 &gt; 0)\n {\n #ifdef _OPENMP\n #pragma omp for lastprivate(__pyx_v_k) firstprivate(__pyx_v_i) lastprivate(__pyx_v_i) lastprivate(__pyx_v_slp) lastprivate(__pyx_v_j) lastprivate(__pyx_v_dzdy) lastprivate(__pyx_v_dzdx) schedule(dynamic)\n #endif /* _OPENMP */\n for (__pyx_t_2 = 0; __pyx_t_2 &lt; __pyx_t_3; __pyx_t_2++){\n {\n __pyx_v_i = 0 + 1 * __pyx_t_2;\n /* Initialize private variables to invalid values */\n __pyx_v_k = ((double)__PYX_NAN());\n __pyx_v_slp = ((double)__PYX_NAN());\n __pyx_v_j = ((int)0xbad0bad0);\n __pyx_v_dzdy = ((double)__PYX_NAN());\n __pyx_v_dzdx = ((double)__PYX_NAN());\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">15</span>: <span class=\"k\">for</span> <span class=\"n\">j</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"n\">J</span><span class=\"p\">):</span></pre>\n<pre class='cython code score-0 '> __pyx_t_4 = __pyx_v_J;\n for (__pyx_t_5 = 0; __pyx_t_5 &lt; __pyx_t_4; __pyx_t_5+=1) {\n __pyx_v_j = __pyx_t_5;\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">16</span>: <span class=\"n\">dzdx</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">2</span><span class=\"p\">])</span> <span class=\"o\">/</span> <span class=\"mf\">2</span></pre>\n<pre class='cython code score-0 '> __pyx_t_6 = (__pyx_v_i + 1);\n __pyx_t_7 = __pyx_v_j;\n if (__pyx_t_6 &lt; 0) __pyx_t_6 += __pyx_v_indata.shape[0];\n if (__pyx_t_7 &lt; 0) __pyx_t_7 += __pyx_v_indata.shape[1];\n __pyx_t_8 = (__pyx_v_i + 1);\n __pyx_t_9 = (__pyx_v_j + 2);\n if (__pyx_t_8 &lt; 0) __pyx_t_8 += __pyx_v_indata.shape[0];\n if (__pyx_t_9 &lt; 0) __pyx_t_9 += __pyx_v_indata.shape[1];\n __pyx_v_dzdx = (((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_6 * __pyx_v_indata.strides[0]) ) + __pyx_t_7 * __pyx_v_indata.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_8 * __pyx_v_indata.strides[0]) ) + __pyx_t_9 * __pyx_v_indata.strides[1]) )))) / 2.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">17</span>: <span class=\"n\">dzdy</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">]</span> <span class=\"o\">-</span> <span class=\"n\">indata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"o\">+</span><span class=\"mf\">2</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"o\">+</span><span class=\"mf\">1</span><span class=\"p\">])</span> <span class=\"o\">/</span> <span class=\"mf\">2</span></pre>\n<pre class='cython code score-0 '> __pyx_t_10 = __pyx_v_i;\n __pyx_t_11 = (__pyx_v_j + 1);\n if (__pyx_t_10 &lt; 0) __pyx_t_10 += __pyx_v_indata.shape[0];\n if (__pyx_t_11 &lt; 0) __pyx_t_11 += __pyx_v_indata.shape[1];\n __pyx_t_12 = (__pyx_v_i + 2);\n __pyx_t_13 = (__pyx_v_j + 1);\n if (__pyx_t_12 &lt; 0) __pyx_t_12 += __pyx_v_indata.shape[0];\n if (__pyx_t_13 &lt; 0) __pyx_t_13 += __pyx_v_indata.shape[1];\n __pyx_v_dzdy = (((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_10 * __pyx_v_indata.strides[0]) ) + __pyx_t_11 * __pyx_v_indata.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_indata.data + __pyx_t_12 * __pyx_v_indata.strides[0]) ) + __pyx_t_13 * __pyx_v_indata.strides[1]) )))) / 2.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">18</span>: <span class=\"n\">k</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"n\">dzdx</span> <span class=\"o\">*</span> <span class=\"n\">dzdx</span><span class=\"p\">)</span> <span class=\"o\">+</span> <span class=\"p\">(</span><span class=\"n\">dzdy</span> <span class=\"o\">*</span> <span class=\"n\">dzdy</span><span class=\"p\">)</span></pre>\n<pre class='cython code score-0 '> __pyx_v_k = ((__pyx_v_dzdx * __pyx_v_dzdx) + (__pyx_v_dzdy * __pyx_v_dzdy));\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">19</span>: <span class=\"n\">slp</span> <span class=\"o\">=</span> <span class=\"n\">sqrt</span><span class=\"p\">(</span><span class=\"n\">k</span><span class=\"p\">)</span> <span class=\"o\">*</span> <span class=\"mf\">100</span></pre>\n<pre class='cython code score-0 '> __pyx_v_slp = (sqrt(__pyx_v_k) * 100.0);\n</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">20</span>: <span class=\"n\">outdata</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">,</span> <span class=\"n\">j</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"n\">slp</span></pre>\n<pre class='cython code score-0 '> __pyx_t_14 = __pyx_v_i;\n __pyx_t_15 = __pyx_v_j;\n if (__pyx_t_14 &lt; 0) __pyx_t_14 += __pyx_v_outdata.shape[0];\n if (__pyx_t_15 &lt; 0) __pyx_t_15 += __pyx_v_outdata.shape[1];\n *((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_outdata.data + __pyx_t_14 * __pyx_v_outdata.strides[0]) ) + __pyx_t_15 * __pyx_v_outdata.strides[1]) )) = __pyx_v_slp;\n }\n }\n }\n }\n }\n }\n }\n #if ((defined(__APPLE__) || defined(__OSX__)) &amp;&amp; (defined(__GNUC__) &amp;&amp; (__GNUC__ &gt; 2 || (__GNUC__ == 2 &amp;&amp; (__GNUC_MINOR__ &gt; 95)))))\n #undef likely\n #undef unlikely\n #define likely(x) __builtin_expect(!!(x), 1)\n #define unlikely(x) __builtin_expect(!!(x), 0)\n #endif\n }\n</pre></div></body></html>",
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"execution_count": 11
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"cell_type": "code",
"source": "reset_outdata()\n%timeit slope_cython_openmp_sqrt(indata, outdata)",
"execution_count": 12,
"outputs": [
{
"output_type": "stream",
"text": "100 loops, best of 3: 4.45 ms per loop\n",
"name": "stdout"
}
]
}
],
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"name": "python2",
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