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kne42/warp_rc.ipynb

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warp_rc.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import sys\n",
"from scipy import ndimage as ndi, LowLevelCallable"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Definitions"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Warp"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from skimage.transform._warps import _clip_warp_output, convert_to_float, safe_as_int, _to_ndimage_mode, _multichannel_default, warn"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def warp(image, mapping=None, matrix=None, offset=0, output_shape=None,\n",
" out=None, order=1, mode='constant', cval=0, prefilter=None, clip=True,\n",
" preserve_range=False):\n",
" if mapping is not None and matrix is not None:\n",
" raise TypeError(\"'warp' cannot take both 'mapping' and 'matrix'\")\n",
" \n",
" image = convert_to_float(image, preserve_range)\n",
"\n",
" input_shape = np.array(image.shape)\n",
"\n",
" if output_shape is None:\n",
" output_shape = input_shape\n",
" else:\n",
" output_shape = safe_as_int(output_shape)\n",
"\n",
" ndi_mode = _to_ndimage_mode(mode)\n",
" \n",
" if prefilter is None:\n",
" # Pre-filtering not necessary for order 0, 1 interpolation\n",
" prefilter = order > 1\n",
" \n",
" if mapping is not None:\n",
" warped = ndi.geometric_transform(image, mapping, output_shape=output_shape, \n",
" output=out, order=order, mode=ndi_mode, \n",
" cval=cval, prefilter=prefilter)\n",
" elif matrix is not None:\n",
" warped = ndi.affine_transform(image, matrix, output_shape=output_shape,\n",
" output=out, order=order, mode=ndi_mode,\n",
" cval=cval, prefilter=prefilter)\n",
" else:\n",
" raise TypeError(\"'warp' requires either 'mapping' or 'matrix' \"\n",
" \"to be provided\")\n",
" \n",
" if warped is None: # result written directly to `out`\n",
" warped = out\n",
" \n",
" _clip_warp_output(image, warped, order, mode, cval, clip)\n",
"\n",
" return warped"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Cython"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"%load_ext cython"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"warpfile = \"warp101\""
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
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" (__pyx_v_cbdata[__pyx_v_i]) = ((double)__pyx_t_6);\n",
" }\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">37</span>: </pre>\n",
"<pre class=\"cython line score-6\" onclick='toggleDiv(this)'>+<span class=\"\">38</span>: <span class=\"k\">return</span> <span class=\"n\">PyCapsule_New</span><span class=\"p\">(</span><span class=\"o\">&lt;</span><span class=\"n\">void</span><span class=\"o\">*&gt;</span> <span class=\"n\">cbdata</span><span class=\"p\">,</span> <span class=\"bp\">NULL</span><span class=\"p\">,</span> <span class=\"o\">&amp;</span><span class=\"n\">free_ptr</span><span class=\"p\">)</span></pre>\n",
"<pre class='cython code score-6 '> <span class='pyx_macro_api'>__Pyx_XDECREF</span>(__pyx_r);\n",
" __pyx_t_2 = <span class='py_c_api'>PyCapsule_New</span>(((void *)__pyx_v_cbdata), NULL, (&amp;__pyx_f_7warp101_free_ptr));<span class='error_goto'> if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 38, __pyx_L1_error)</span>\n",
" <span class='refnanny'>__Pyx_GOTREF</span>(__pyx_t_2);\n",
" __pyx_r = __pyx_t_2;\n",
" __pyx_t_2 = 0;\n",
" goto __pyx_L0;\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">39</span>: </pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">40</span>: </pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">41</span>: <span class=\"k\">cdef</span> <span class=\"kr\">api</span> <span class=\"kt\">int</span> <span class=\"nf\">_swirl2d</span><span class=\"p\">(</span><span class=\"n\">intptr_t</span><span class=\"o\">*</span> <span class=\"n\">output_coords</span><span class=\"p\">,</span></pre>\n",
"<pre class='cython code score-0 '>static int __pyx_f_7warp101__swirl2d(intptr_t *__pyx_v_output_coords, double *__pyx_v_input_coords, CYTHON_UNUSED int __pyx_v_output_rank, CYTHON_UNUSED int __pyx_v_input_rank, void *__pyx_v_user_data) {\n",
" double *__pyx_v_args;\n",
" double __pyx_v_r;\n",
" double __pyx_v_c;\n",
" double __pyx_v_r0;\n",
" double __pyx_v_c0;\n",
" double __pyx_v_rotation;\n",
" double __pyx_v_strength;\n",
" double __pyx_v_radius;\n",
" double __pyx_v_rho;\n",
" double __pyx_v_theta;\n",
" int __pyx_r;\n",
" <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n",
" <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"_swirl2d\", 0);\n",
"/* … */\n",
" /* function exit code */\n",
" __pyx_L0:;\n",
" <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n",
" return __pyx_r;\n",
"}\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">42</span>: <span class=\"n\">double</span><span class=\"o\">*</span> <span class=\"n\">input_coords</span><span class=\"p\">,</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">43</span>: <span class=\"nb\">int</span> <span class=\"n\">output_rank</span><span class=\"p\">,</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">44</span>: <span class=\"nb\">int</span> <span class=\"n\">input_rank</span><span class=\"p\">,</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">45</span>: <span class=\"n\">void</span><span class=\"o\">*</span> <span class=\"n\">user_data</span><span class=\"p\">):</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">46</span>: <span class=\"sd\">&quot;&quot;&quot;2D swirl mapping function&quot;&quot;&quot;</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">47</span>: <span class=\"k\">cdef</span><span class=\"p\">:</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">48</span>: <span class=\"n\">Py_ssize_t</span> <span class=\"n\">i</span></pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">49</span>: <span class=\"n\">double</span><span class=\"o\">*</span> <span class=\"n\">args</span> <span class=\"o\">=</span> <span class=\"o\">&lt;</span><span class=\"n\">double</span><span class=\"o\">*&gt;</span> <span class=\"n\">user_data</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_args = ((double *)__pyx_v_user_data);\n",
"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">50</span>: <span class=\"n\">double</span> <span class=\"n\">r</span> <span class=\"o\">=</span> <span class=\"p\">&lt;</span><span class=\"kt\">double</span><span class=\"p\">&gt;</span> <span class=\"n\">output_coords</span><span class=\"p\">[</span><span class=\"mf\">0</span><span class=\"p\">]</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_r = ((double)(__pyx_v_output_coords[0]));\n",
"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">51</span>: <span class=\"n\">double</span> <span class=\"n\">c</span> <span class=\"o\">=</span> <span class=\"p\">&lt;</span><span class=\"kt\">double</span><span class=\"p\">&gt;</span> <span class=\"n\">output_coords</span><span class=\"p\">[</span><span class=\"mf\">1</span><span class=\"p\">]</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_c = ((double)(__pyx_v_output_coords[1]));\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">52</span>: </pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">53</span>: <span class=\"n\">double</span> <span class=\"n\">r0</span> <span class=\"o\">=</span> <span class=\"n\">args</span><span class=\"p\">[</span><span class=\"mf\">0</span><span class=\"p\">]</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_r0 = (__pyx_v_args[0]);\n",
"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">54</span>: <span class=\"n\">double</span> <span class=\"n\">c0</span> <span class=\"o\">=</span> <span class=\"n\">args</span><span class=\"p\">[</span><span class=\"mf\">1</span><span class=\"p\">]</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_c0 = (__pyx_v_args[1]);\n",
"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">55</span>: <span class=\"n\">double</span> <span class=\"n\">rotation</span> <span class=\"o\">=</span> <span class=\"n\">args</span><span class=\"p\">[</span><span class=\"mf\">2</span><span class=\"p\">]</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_rotation = (__pyx_v_args[2]);\n",
"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">56</span>: <span class=\"n\">double</span> <span class=\"n\">strength</span> <span class=\"o\">=</span> <span class=\"n\">args</span><span class=\"p\">[</span><span class=\"mf\">3</span><span class=\"p\">]</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_strength = (__pyx_v_args[3]);\n",
"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">57</span>: <span class=\"n\">double</span> <span class=\"n\">radius</span> <span class=\"o\">=</span> <span class=\"n\">args</span><span class=\"p\">[</span><span class=\"mf\">4</span><span class=\"p\">]</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_radius = (__pyx_v_args[4]);\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">58</span>: </pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">59</span>: <span class=\"n\">double</span> <span class=\"n\">rho</span><span class=\"p\">,</span> <span class=\"n\">theta</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">60</span>: </pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">61</span>: <span class=\"n\">rho</span> <span class=\"o\">=</span> <span class=\"n\">math</span><span class=\"o\">.</span><span class=\"n\">hypot</span><span class=\"p\">(</span><span class=\"n\">r</span> <span class=\"o\">-</span> <span class=\"n\">r0</span><span class=\"p\">,</span> <span class=\"n\">c</span> <span class=\"o\">-</span> <span class=\"n\">c0</span><span class=\"p\">)</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_rho = hypot((__pyx_v_r - __pyx_v_r0), (__pyx_v_c - __pyx_v_c0));\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">62</span>: </pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">63</span>: <span class=\"c\"># Ensure that the transformation decays to approximately 1/1000-th</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">64</span>: <span class=\"c\"># within the specified radius.</span></pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">65</span>: <span class=\"n\">radius</span> <span class=\"o\">=</span> <span class=\"n\">radius</span> <span class=\"o\">/</span> <span class=\"mf\">5</span> <span class=\"o\">*</span> <span class=\"n\">math</span><span class=\"o\">.</span><span class=\"n\">log</span><span class=\"p\">(</span><span class=\"mf\">2</span><span class=\"p\">)</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_radius = ((__pyx_v_radius / 5.0) * log(2.0));\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">66</span>: </pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">67</span>: <span class=\"n\">theta</span> <span class=\"o\">=</span> <span class=\"n\">rotation</span> <span class=\"o\">+</span> <span class=\"n\">strength</span> <span class=\"o\">*</span> <span class=\"n\">math</span><span class=\"o\">.</span><span class=\"n\">exp</span><span class=\"p\">(</span><span class=\"o\">-</span><span class=\"n\">rho</span> <span class=\"o\">/</span> <span class=\"n\">radius</span><span class=\"p\">)</span> <span class=\"o\">+</span> <span class=\"n\">math</span><span class=\"o\">.</span><span class=\"n\">atan2</span><span class=\"p\">(</span><span class=\"n\">r</span> <span class=\"o\">-</span> <span class=\"n\">r0</span><span class=\"p\">,</span> <span class=\"n\">c</span> <span class=\"o\">-</span> <span class=\"n\">c0</span><span class=\"p\">)</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_theta = ((__pyx_v_rotation + (__pyx_v_strength * exp(((-__pyx_v_rho) / __pyx_v_radius)))) + atan2((__pyx_v_r - __pyx_v_r0), (__pyx_v_c - __pyx_v_c0)));\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">68</span>: </pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">69</span>: <span class=\"n\">input_coords</span><span class=\"p\">[</span><span class=\"mf\">0</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"n\">r0</span> <span class=\"o\">+</span> <span class=\"n\">rho</span> <span class=\"o\">*</span> <span class=\"n\">math</span><span class=\"o\">.</span><span class=\"n\">sin</span><span class=\"p\">(</span><span class=\"n\">theta</span><span class=\"p\">)</span></pre>\n",
"<pre class='cython code score-0 '> (__pyx_v_input_coords[0]) = (__pyx_v_r0 + (__pyx_v_rho * sin(__pyx_v_theta)));\n",
"</pre><pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">70</span>: <span class=\"n\">input_coords</span><span class=\"p\">[</span><span class=\"mf\">1</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"n\">c0</span> <span class=\"o\">+</span> <span class=\"n\">rho</span> <span class=\"o\">*</span> <span class=\"n\">math</span><span class=\"o\">.</span><span class=\"n\">cos</span><span class=\"p\">(</span><span class=\"n\">theta</span><span class=\"p\">)</span></pre>\n",
"<pre class='cython code score-0 '> (__pyx_v_input_coords[1]) = (__pyx_v_c0 + (__pyx_v_rho * cos(__pyx_v_theta)));\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">71</span>: </pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">72</span>: <span class=\"k\">return</span> <span class=\"mf\">1</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_r = 1;\n",
" goto __pyx_L0;\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">73</span>: </pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">74</span>: </pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">75</span>: <span class=\"k\">cdef</span> <span class=\"kr\">api</span> <span class=\"kt\">int</span> <span class=\"nf\">_rescale</span><span class=\"p\">(</span><span class=\"n\">intptr_t</span><span class=\"o\">*</span> <span class=\"n\">output_coords</span><span class=\"p\">,</span></pre>\n",
"<pre class='cython code score-0 '>static int __pyx_f_7warp101__rescale(intptr_t *__pyx_v_output_coords, double *__pyx_v_input_coords, int __pyx_v_output_rank, CYTHON_UNUSED int __pyx_v_input_rank, void *__pyx_v_user_data) {\n",
" Py_ssize_t __pyx_v_i;\n",
" double *__pyx_v_factors;\n",
" int __pyx_r;\n",
" <span class='refnanny'>__Pyx_RefNannyDeclarations</span>\n",
" <span class='refnanny'>__Pyx_RefNannySetupContext</span>(\"_rescale\", 0);\n",
"/* … */\n",
" /* function exit code */\n",
" __pyx_L0:;\n",
" <span class='refnanny'>__Pyx_RefNannyFinishContext</span>();\n",
" return __pyx_r;\n",
"}\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">76</span>: <span class=\"n\">double</span><span class=\"o\">*</span> <span class=\"n\">input_coords</span><span class=\"p\">,</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">77</span>: <span class=\"nb\">int</span> <span class=\"n\">output_rank</span><span class=\"p\">,</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">78</span>: <span class=\"nb\">int</span> <span class=\"n\">input_rank</span><span class=\"p\">,</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">79</span>: <span class=\"n\">void</span><span class=\"o\">*</span> <span class=\"n\">user_data</span><span class=\"p\">):</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">80</span>: <span class=\"sd\">&quot;&quot;&quot;Rescale mapping function&quot;&quot;&quot;</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">81</span>: <span class=\"k\">cdef</span><span class=\"p\">:</span></pre>\n",
"<pre class=\"cython line score-0\">&#xA0;<span class=\"\">82</span>: <span class=\"n\">Py_ssize_t</span> <span class=\"n\">i</span></pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">83</span>: <span class=\"n\">double</span><span class=\"o\">*</span> <span class=\"n\">factors</span> <span class=\"o\">=</span> <span class=\"o\">&lt;</span><span class=\"n\">double</span><span class=\"o\">*&gt;</span> <span class=\"n\">user_data</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_v_factors = ((double *)__pyx_v_user_data);\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">84</span>: </pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">85</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\">output_rank</span><span class=\"p\">):</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_t_1 = __pyx_v_output_rank;\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=\"\">86</span>: <span class=\"n\">input_coords</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"p\">&lt;</span><span class=\"kt\">double</span><span class=\"p\">&gt;</span> <span class=\"n\">output_coords</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">]</span> <span class=\"o\">*</span> <span class=\"n\">factors</span><span class=\"p\">[</span><span class=\"n\">i</span><span class=\"p\">]</span></pre>\n",
"<pre class='cython code score-0 '> (__pyx_v_input_coords[__pyx_v_i]) = (((double)(__pyx_v_output_coords[__pyx_v_i])) * (__pyx_v_factors[__pyx_v_i]));\n",
" }\n",
"</pre><pre class=\"cython line score-0\">&#xA0;<span class=\"\">87</span>: </pre>\n",
"<pre class=\"cython line score-0\" onclick='toggleDiv(this)'>+<span class=\"\">88</span>: <span class=\"k\">return</span> <span class=\"mf\">1</span></pre>\n",
"<pre class='cython code score-0 '> __pyx_r = 1;\n",
" goto __pyx_L0;\n",
"</pre></div></body></html>"
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"<IPython.core.display.HTML object>"
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"source": [
"%%cython -a -n {warpfile}\n",
"#cython: boundscheck=False\n",
"#cython: wraparound=False\n",
"#cython: cdivision=True\n",
"#cython: nonecheck=False\n",
"#cython: initializedcheck=False\n",
"#cython: binding=False\n",
"#cython: infer_types=False\n",
"\n",
"import sys\n",
"\n",
"import numpy as np\n",
"cimport numpy as cnp\n",
"\n",
"from scipy import LowLevelCallable\n",
"\n",
"from cpython.pycapsule cimport *\n",
"\n",
"from libc.stdint cimport intptr_t\n",
"from libc.stdlib cimport malloc, free\n",
"from libc cimport math\n",
"\n",
"\n",
"cdef void free_ptr(object capsule):\n",
" free(PyCapsule_GetPointer(capsule, NULL))\n",
"\n",
"\n",
"def user_data(*data):\n",
" cdef:\n",
" Py_ssize_t i\n",
" double *cbdata = <double*> malloc(len(data) * sizeof(double))\n",
" \n",
" if not user_data:\n",
" raise MemoryError()\n",
" \n",
" for i in range(len(data)):\n",
" cbdata[i] = <double> data[i]\n",
" \n",
" return PyCapsule_New(<void*> cbdata, NULL, &free_ptr)\n",
"\n",
"\n",
"cdef api int _swirl2d(intptr_t* output_coords,\n",
" double* input_coords,\n",
" int output_rank,\n",
" int input_rank,\n",
" void* user_data):\n",
" \"\"\"2D swirl mapping function\"\"\"\n",
" cdef:\n",
" Py_ssize_t i\n",
" double* args = <double*> user_data\n",
" double r = <double> output_coords[0]\n",
" double c = <double> output_coords[1]\n",
" \n",
" double r0 = args[0]\n",
" double c0 = args[1]\n",
" double rotation = args[2]\n",
" double strength = args[3]\n",
" double radius = args[4]\n",
" \n",
" double rho, theta\n",
"\n",
" rho = math.hypot(r - r0, c - c0)\n",
"\n",
" # Ensure that the transformation decays to approximately 1/1000-th\n",
" # within the specified radius.\n",
" radius = radius / 5 * math.log(2)\n",
"\n",
" theta = rotation + strength * math.exp(-rho / radius) + math.atan2(r - r0, c - c0)\n",
"\n",
" input_coords[0] = r0 + rho * math.sin(theta)\n",
" input_coords[1] = c0 + rho * math.cos(theta)\n",
"\n",
" return 1\n",
"\n",
"\n",
"cdef api int _rescale(intptr_t* output_coords,\n",
" double* input_coords,\n",
" int output_rank,\n",
" int input_rank,\n",
" void* user_data):\n",
" \"\"\"Rescale mapping function\"\"\"\n",
" cdef:\n",
" Py_ssize_t i\n",
" double* factors = <double*> user_data\n",
" \n",
" for i in range(output_rank):\n",
" input_coords[i] = <double> output_coords[i] * factors[i]\n",
" \n",
" return 1"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"__import__(warpfile)\n",
"_warps_cy = sys.modules[warpfile]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Swirl"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"def swirl(image, center=None, strength=1, radius=100, rotation=0,\n",
" output_shape=None, order=1, mode=None, cval=0, clip=True,\n",
" preserve_range=False, out=None):\n",
" if mode is None:\n",
" warn('The default of `mode` in `skimage.transform.swirl` '\n",
" 'will change to `reflect` in version 0.15.')\n",
" mode = 'constant'\n",
"\n",
" if center is None:\n",
" center = np.array(image.shape)[:2][::-1] / 2\n",
" \n",
" cbdata = user_data(center[0], center[1],\n",
" rotation, strength, radius)\n",
"\n",
" llc = LowLevelCallable.from_cython(_warps_cy, '_swirl2d',\n",
" user_data=cbdata)\n",
"\n",
" return warp(image, mapping=llc, out=out, output_shape=output_shape,\n",
" order=order, mode=mode, cval=cval,\n",
" clip=clip, preserve_range=preserve_range)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Resize/Rescale"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"def resize_geometric(image, output_shape, order=1, mode='constant', cval=0, clip=True,\n",
" preserve_range=False, anti_aliasing=True, anti_aliasing_sigma=None,\n",
" out=None):\n",
" output_shape = tuple(output_shape)\n",
" output_ndim = len(output_shape)\n",
" input_shape = image.shape\n",
" if output_ndim > image.ndim:\n",
" # append dimensions to input_shape\n",
" input_shape = input_shape + (1, ) * (output_ndim - image.ndim)\n",
" image = np.reshape(image, input_shape)\n",
" elif output_ndim == image.ndim - 1:\n",
" # multichannel case: append shape of last axis\n",
" output_shape = output_shape + (image.shape[-1], )\n",
" elif output_ndim < image.ndim - 1:\n",
" raise ValueError(\"len(output_shape) cannot be smaller than the image \"\n",
" \"dimensions\")\n",
"\n",
" factors = (np.array(input_shape, dtype=float) /\n",
" np.array(output_shape, dtype=float))\n",
"\n",
" if anti_aliasing:\n",
" if anti_aliasing_sigma is None:\n",
" anti_aliasing_sigma = np.maximum(0, (factors - 1) / 2)\n",
" else:\n",
" anti_aliasing_sigma = \\\n",
" np.atleast_1d(anti_aliasing_sigma) * np.ones_like(factors)\n",
" if np.any(anti_aliasing_sigma < 0):\n",
" raise ValueError(\"Anti-aliasing standard deviation must be \"\n",
" \"greater than or equal to zero\")\n",
" elif np.any((anti_aliasing_sigma > 0) & (factors <= 1)):\n",
" warn(\"Anti-aliasing standard deviation greater than zero but \"\n",
" \"not down-sampling along all axes\")\n",
"\n",
" image = ndi.gaussian_filter(image, anti_aliasing_sigma,\n",
" cval=cval, mode=mode)\n",
"\n",
" cbdata = user_data(*factors)\n",
" llc = LowLevelCallable.from_cython(_warps_cy, '_rescale',\n",
" user_data=cbdata)\n",
" \n",
" return warp(image, mapping=llc, output_shape=output_shape, out=out,\n",
" order=order, mode=mode, cval=cval, prefilter=False,\n",
" clip=clip, preserve_range=preserve_range)\n",
"\n",
"\n",
"def rescale_geometric(image, scale, order=1, mode='constant', cval=0, clip=True,\n",
" preserve_range=False, multichannel=None,\n",
" anti_aliasing=True, anti_aliasing_sigma=None, out=None):\n",
" multichannel = _multichannel_default(multichannel, image.ndim)\n",
" scale = np.atleast_1d(scale)\n",
" if len(scale) > 1:\n",
" if ((not multichannel and len(scale) != image.ndim) or\n",
" (multichannel and len(scale) != image.ndim - 1)):\n",
" raise ValueError(\"Supply a single scale, or one value per spatial \"\n",
" \"axis\")\n",
" if multichannel:\n",
" scale = np.concatenate((scale, [1]))\n",
" orig_shape = np.asarray(image.shape)\n",
" output_shape = np.round(scale * orig_shape)\n",
" if multichannel: # don't scale channel dimension\n",
" output_shape[-1] = orig_shape[-1]\n",
"\n",
" return resize_geometric(image, output_shape, out=out, order=order,\n",
" mode=mode, cval=cval, clip=clip,\n",
" preserve_range=preserve_range,\n",
" anti_aliasing=anti_aliasing,\n",
" anti_aliasing_sigma=anti_aliasing_sigma)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"def resize_affine(image, output_shape, order=1, mode='constant', cval=0, clip=True,\n",
" preserve_range=False, anti_aliasing=True, anti_aliasing_sigma=None,\n",
" out=None):\n",
" output_shape = tuple(output_shape)\n",
" output_ndim = len(output_shape)\n",
" input_shape = image.shape\n",
" if output_ndim > image.ndim:\n",
" # append dimensions to input_shape\n",
" input_shape = input_shape + (1, ) * (output_ndim - image.ndim)\n",
" image = np.reshape(image, input_shape)\n",
" elif output_ndim == image.ndim - 1:\n",
" # multichannel case: append shape of last axis\n",
" output_shape = output_shape + (image.shape[-1], )\n",
" elif output_ndim < image.ndim - 1:\n",
" raise ValueError(\"len(output_shape) cannot be smaller than the image \"\n",
" \"dimensions\")\n",
"\n",
" factors = (np.array(input_shape, dtype=float) /\n",
" np.array(output_shape, dtype=float))\n",
"\n",
" if anti_aliasing:\n",
" if anti_aliasing_sigma is None:\n",
" anti_aliasing_sigma = np.maximum(0, (factors - 1) / 2)\n",
" else:\n",
" anti_aliasing_sigma = \\\n",
" np.atleast_1d(anti_aliasing_sigma) * np.ones_like(factors)\n",
" if np.any(anti_aliasing_sigma < 0):\n",
" raise ValueError(\"Anti-aliasing standard deviation must be \"\n",
" \"greater than or equal to zero\")\n",
" elif np.any((anti_aliasing_sigma > 0) & (factors <= 1)):\n",
" warn(\"Anti-aliasing standard deviation greater than zero but \"\n",
" \"not down-sampling along all axes\")\n",
"\n",
" image = ndi.gaussian_filter(image, anti_aliasing_sigma,\n",
" cval=cval, mode=mode)\n",
"\n",
" return warp(image, matrix=np.diag(factors), output_shape=output_shape,\n",
" out=out, order=order, mode=mode, cval=cval, prefilter=False,\n",
" clip=clip, preserve_range=preserve_range)\n",
"\n",
"\n",
"def rescale_affine(image, scale, order=1, mode='constant', cval=0, clip=True,\n",
" preserve_range=False, multichannel=None,\n",
" anti_aliasing=True, anti_aliasing_sigma=None, out=None):\n",
" multichannel = _multichannel_default(multichannel, image.ndim)\n",
" scale = np.atleast_1d(scale)\n",
" if len(scale) > 1:\n",
" if ((not multichannel and len(scale) != image.ndim) or\n",
" (multichannel and len(scale) != image.ndim - 1)):\n",
" raise ValueError(\"Supply a single scale, or one value per spatial \"\n",
" \"axis\")\n",
" if multichannel:\n",
" scale = np.concatenate((scale, [1]))\n",
" orig_shape = np.asarray(image.shape)\n",
" output_shape = np.round(scale * orig_shape)\n",
" if multichannel: # don't scale channel dimension\n",
" output_shape[-1] = orig_shape[-1]\n",
"\n",
" return resize_affine(image, output_shape, order=order, mode=mode, cval=cval,\n",
" clip=clip, preserve_range=preserve_range,\n",
" anti_aliasing=anti_aliasing,\n",
" anti_aliasing_sigma=anti_aliasing_sigma, out=out)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Rotate"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"def rotate_geometric(image, angle, plane=(0, 1), resize=False, center=None, order=1, mode='constant',\n",
" cval=0, clip=True, preserve_range=False, out=None):\n",
" # rotation around center\n",
" if center is None:\n",
" center = np.asarray(image.shape) / 2\n",
" else:\n",
" center = np.asarray(center)\n",
"\n",
" return warp(image, tform, output_shape=output_shape, order=order,\n",
" mode=mode, cval=cval, clip=clip, preserve_range=preserve_range)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"def rotate(image, angle, plane=(0, 1), axis=None, resize=False, out=None, center=None,\n",
" order=1, mode='constant', cval=0, clip=True, preserve_range=False):\n",
" # rotation around center\n",
" if center is None:\n",
" center = np.asarray(np.shape(image)) / 2\n",
" else:\n",
" center = np.asarray(center)\n",
" \n",
" matrix = np.eye(np.ndim(image))\n",
" matrix[plane[0], plane[0]] = np.cos(angle)\n",
" matrix[plane[0], plane[1]] = -np.sin(angle)\n",
" matrix[plane[1], plane[0]] = np.sin(angle)\n",
" matrix[plane[1], plane[1]] = np.cos(angle)\n",
" \n",
" output_shape = np.shape(image)\n",
" if resize:\n",
" pass\n",
"\n",
" return warp(image, matrix=matrix, output_shape=output_shape, offset=center,\n",
" order=order, mode=mode, cval=cval, clip=clip,\n",
" preserve_range=preserve_range)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Tests"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"from skimage import data"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"cam = data.camera()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"from matplotlib import pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Swirl"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"cam_swirled = swirl(cam, mode='constant', radius=500, strength=5)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x1c114300f0>"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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mQ+6SZ1wMZvenF4HStTRSDkDbLPr8M9yFUNRwVDCYLMkyyX7RoyD5zntBHLok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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1c10ec2668>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(cam_swirled)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"from skimage import transform as curr"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"cam_swirled = curr.swirl(cam, mode='constant', radius=500, strength=5)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x1c11719f98>"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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mQ+6SZ1wMZvenF4HStTRSDkDbLPr8M9yFUNRwVDCYLMkyyX7RoyD5zntBHLok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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1c1140ec50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(cam_swirled)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Resize/Rescale"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"cam_resized = resize_geometric(cam, (1024, 256), mode='constant', anti_aliasing=False)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x1c11802160>"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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MM0pVCK299dNY2fxluEGVKPt8ghkAHBxtxkx+bltq2mgGY/tlJzwjYC2bb5hG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\naPcG7S1o/x90f7iQ4kxdpQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1c10e86eb8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(cam_resized)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"cam_resized = resize_affine(cam, (1024, 256), mode='constant', anti_aliasing=False)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x1c11775860>"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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MM0pVCK299dNY2fxluEGVKPt8ghkAHBxtxkx+bltq2mgGY/tlJzwjYC2bb5hG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\naPcG7S1o/x90f7iQ4kxdpQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1c117d7cf8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(cam_resized)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"cam_resized = curr.resize(cam, (1024, 256), mode='constant', anti_aliasing=False)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x1c12b5f0b8>"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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E9aLsXa+0q2PsWY84x22/HJp7pKqgaTj1i09zx5+9zB3feoXfat6EHp2hOgXv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\nYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1c117e5518>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(cam_resized)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Benchmarks"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Swirl"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"57.4 ms ± 2.64 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
]
}
],
"source": [
"# geometric\n",
"%timeit swirl(cam, mode='constant', radius=500, strength=5)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"37.9 ms ± 669 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
]
}
],
"source": [
"# map_coordinates\n",
"%timeit curr.swirl(cam, mode='constant', radius=500, strength=5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Resize/Rescale"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"41.7 ms ± 1.91 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
]
}
],
"source": [
"# geometric\n",
"%timeit resize_geometric(cam, (1024, 256), mode='constant', anti_aliasing=False)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"18.2 ms ± 849 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
]
}
],
"source": [
"# affine\n",
"%timeit resize_affine(cam, (1024, 256), mode='constant', anti_aliasing=False)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"8.3 ms ± 303 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
]
}
],
"source": [
"# map_coordinates\n",
"%timeit curr.resize(cam, (1024, 256), mode='constant', anti_aliasing=False)"
]
}
],
"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": "3.6.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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