From 8f4dcac780723bb91eeda805c04eb81b687e4b38 2015-01-30 21:57:37 From: Min RK Date: 2015-01-30 21:57:37 Subject: [PATCH] add kernel metadata to example notebooks --- diff --git a/examples/Customization/Index.ipynb b/examples/Customization/Index.ipynb index 1cc59c2..c9043b3 100644 --- a/examples/Customization/Index.ipynb +++ b/examples/Customization/Index.ipynb @@ -95,7 +95,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Embedding/Index.ipynb b/examples/Embedding/Index.ipynb index 1652f15..ae87ef1 100644 --- a/examples/Embedding/Index.ipynb +++ b/examples/Embedding/Index.ipynb @@ -186,7 +186,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Animations Using clear_output.ipynb b/examples/IPython Kernel/Animations Using clear_output.ipynb index 8b59c77..ae4813e 100644 --- a/examples/IPython Kernel/Animations Using clear_output.ipynb +++ b/examples/IPython Kernel/Animations Using clear_output.ipynb @@ -1335,7 +1335,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Background Jobs.ipynb b/examples/IPython Kernel/Background Jobs.ipynb index 2d8b7f5..33175cd 100644 --- a/examples/IPython Kernel/Background Jobs.ipynb +++ b/examples/IPython Kernel/Background Jobs.ipynb @@ -380,7 +380,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Beyond Plain Python.ipynb b/examples/IPython Kernel/Beyond Plain Python.ipynb index 984dee2..abc7fbe 100644 --- a/examples/IPython Kernel/Beyond Plain Python.ipynb +++ b/examples/IPython Kernel/Beyond Plain Python.ipynb @@ -162,7 +162,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Tab completion, especially for attributes, is a convenient way to explore the structure of any object you\u2019re dealing with. Simply type `object_name.` to view the object\u2019s attributes. Besides Python objects and keywords, tab completion also works on file and directory names." + "Tab completion, especially for attributes, is a convenient way to explore the structure of any object you’re dealing with. Simply type `object_name.` to view the object’s attributes. Besides Python objects and keywords, tab completion also works on file and directory names." ] }, { @@ -721,9 +721,9 @@ "text": [ "size: 010000000 loops, best of 3: 129 ns per loop\n", " size: 1001000000 loops, best of 3: 649 ns per loop\n", - " size: 2001000000 loops, best of 3: 1.09 \u00b5s per loop\n", - " size: 3001000000 loops, best of 3: 1.74 \u00b5s per loop\n", - " size: 400100000 loops, best of 3: 2.72 \u00b5s per loop\n", + " size: 2001000000 loops, best of 3: 1.09 µs per loop\n", + " size: 3001000000 loops, best of 3: 1.74 µs per loop\n", + " size: 400100000 loops, best of 3: 2.72 µs per loop\n", "\n" ] } @@ -1799,7 +1799,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Capturing Output.ipynb b/examples/IPython Kernel/Capturing Output.ipynb index ff0f7c9..14ba994 100644 --- a/examples/IPython Kernel/Capturing Output.ipynb +++ b/examples/IPython Kernel/Capturing Output.ipynb @@ -481,7 +481,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Cell Magics.ipynb b/examples/IPython Kernel/Cell Magics.ipynb index f7dc4a2..78cc6ec 100644 --- a/examples/IPython Kernel/Cell Magics.ipynb +++ b/examples/IPython Kernel/Cell Magics.ipynb @@ -693,7 +693,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Custom Display Logic.ipynb b/examples/IPython Kernel/Custom Display Logic.ipynb index 4f40795..b26696b 100644 --- a/examples/IPython Kernel/Custom Display Logic.ipynb +++ b/examples/IPython Kernel/Custom Display Logic.ipynb @@ -1317,7 +1317,25 @@ "source": [] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Index.ipynb b/examples/IPython Kernel/Index.ipynb index f674914..cceeeb7 100644 --- a/examples/IPython Kernel/Index.ipynb +++ b/examples/IPython Kernel/Index.ipynb @@ -160,7 +160,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Old Custom Display Logic.ipynb b/examples/IPython Kernel/Old Custom Display Logic.ipynb index b147242..a4c7cbc 100644 --- a/examples/IPython Kernel/Old Custom Display Logic.ipynb +++ b/examples/IPython Kernel/Old Custom Display Logic.ipynb @@ -586,9 +586,9 @@ "$$\\frac{3}{2} \\pi + \\frac{e^{\\mathbf{\\imath} x}}{x^{2} + y}$$" ], "text/plain": [ - " \u2148\u22c5x \n", - "3\u22c5\u03c0 \u212f \n", - "\u2500\u2500\u2500 + \u2500\u2500\u2500\u2500\u2500\u2500\n", + " ⅈ⋅x \n", + "3⋅π ℯ \n", + "─── + ──────\n", " 2 2 \n", " x + y" ] @@ -1477,7 +1477,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Plotting in the Notebook.ipynb b/examples/IPython Kernel/Plotting in the Notebook.ipynb index 0d09126..a20b274 100644 --- a/examples/IPython Kernel/Plotting in the Notebook.ipynb +++ b/examples/IPython Kernel/Plotting in the Notebook.ipynb @@ -732,7 +732,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Raw Input in the Notebook.ipynb b/examples/IPython Kernel/Raw Input in the Notebook.ipynb index 78cf9bd..e84e0e6 100644 --- a/examples/IPython Kernel/Raw Input in the Notebook.ipynb +++ b/examples/IPython Kernel/Raw Input in the Notebook.ipynb @@ -150,7 +150,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Rich Output.ipynb b/examples/IPython Kernel/Rich Output.ipynb index 9cbf86b..8e80055 100644 --- a/examples/IPython Kernel/Rich Output.ipynb +++ b/examples/IPython Kernel/Rich Output.ipynb @@ -3051,7 +3051,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Script Magics.ipynb b/examples/IPython Kernel/Script Magics.ipynb index 7d362e6..8cce438 100644 --- a/examples/IPython Kernel/Script Magics.ipynb +++ b/examples/IPython Kernel/Script Magics.ipynb @@ -442,7 +442,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/SymPy.ipynb b/examples/IPython Kernel/SymPy.ipynb index 68172fa..74da7d4 100644 --- a/examples/IPython Kernel/SymPy.ipynb +++ b/examples/IPython Kernel/SymPy.ipynb @@ -54,9 +54,9 @@ "$$\\frac{3 \\pi}{2} + \\frac{e^{i x}}{x^{2} + y}$$" ], "text/plain": [ - " \u2148\u22c5x \n", - "3\u22c5\u03c0 \u212f \n", - "\u2500\u2500\u2500 + \u2500\u2500\u2500\u2500\u2500\u2500\n", + " ⅈ⋅x \n", + "3⋅π ℯ \n", + "─── + ──────\n", " 2 2 \n", " x + y" ] @@ -174,7 +174,7 @@ ], "text/plain": [ " 2\n", - "(x + 1)\u22c5(x + y) " + "(x + 1)⋅(x + y) " ] }, "execution_count": 7, @@ -201,7 +201,7 @@ ], "text/plain": [ " 3 2 2 2 2\n", - "x + 2\u22c5x \u22c5y + x + x\u22c5y + 2\u22c5x\u22c5y + y " + "x + 2⋅x ⋅y + x + x⋅y + 2⋅x⋅y + y " ] }, "execution_count": 8, @@ -226,8 +226,8 @@ "$$\\frac{1}{x} \\left(x \\sin{\\left (x \\right )} - 1\\right) + \\frac{1}{x}$$" ], "text/plain": [ - "x\u22c5sin(x) - 1 1\n", - "\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500 + \u2500\n", + "x⋅sin(x) - 1 1\n", + "──────────── + ─\n", " x x" ] }, @@ -280,7 +280,7 @@ ], "text/plain": [ " 3 2 \n", - "x + 2\u22c5x + 4\u22c5x + 8 = 0" + "x + 2⋅x + 4⋅x + 8 = 0" ] }, "execution_count": 11, @@ -306,7 +306,7 @@ "$$\\begin{bmatrix}-2, & - 2 i, & 2 i\\end{bmatrix}$$" ], "text/plain": [ - "[-2, -2\u22c5\u2148, 2\u22c5\u2148]" + "[-2, -2⋅ⅈ, 2⋅ⅈ]" ] }, "execution_count": 12, @@ -333,11 +333,11 @@ "text/plain": [ " b \n", " ___ \n", - " \u2572 \n", - " \u2572 \u239b n 2\u239e\n", - " \u2571 \u239d2 + 6\u22c5n \u23a0\n", - " \u2571 \n", - " \u203e\u203e\u203e \n", + " ╲ \n", + " ╲ ⎛ n 2⎞\n", + " ╱ ⎝2 + 6⋅n ⎠\n", + " ╱ \n", + " ‾‾‾ \n", "n = a " ] }, @@ -397,8 +397,8 @@ ], "text/plain": [ " 2 4 \n", - " x 5\u22c5x \u239b 6\u239e\n", - "1 + \u2500\u2500 + \u2500\u2500\u2500\u2500 + O\u239dx \u23a0\n", + " x 5⋅x ⎛ 6⎞\n", + "1 + ── + ──── + O⎝x ⎠\n", " 2 24 " ] }, @@ -424,9 +424,9 @@ "$$- \\frac{4 x \\cos{\\left (x^{2} \\right )}}{x + 1} \\sin{\\left (x^{2} \\right )} - \\frac{\\cos^{2}{\\left (x^{2} \\right )}}{\\left(x + 1\\right)^{2}}$$" ], "text/plain": [ - " \u239b 2\u239e \u239b 2\u239e 2\u239b 2\u239e\n", - " 4\u22c5x\u22c5sin\u239dx \u23a0\u22c5cos\u239dx \u23a0 cos \u239dx \u23a0\n", - "- \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500 - \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n", + " ⎛ 2⎞ ⎛ 2⎞ 2⎛ 2⎞\n", + " 4⋅x⋅sin⎝x ⎠⋅cos⎝x ⎠ cos ⎝x ⎠\n", + "- ─────────────────── - ────────\n", " x + 1 2\n", " (x + 1) " ] @@ -454,8 +454,8 @@ ], "text/plain": [ " 2\n", - " \u03c0 \n", - "-2 + \u2500\u2500\n", + " π \n", + "-2 + ──\n", " 4 " ] }, @@ -483,7 +483,7 @@ "text/plain": [ " 2 \n", " d \n", - "9\u22c5f(x) + \u2500\u2500\u2500(f(x)) = 1\n", + "9⋅f(x) + ───(f(x)) = 1\n", " 2 \n", " dx " ] @@ -497,7 +497,7 @@ "$$f{\\left (x \\right )} = C_{1} \\sin{\\left (3 x \\right )} + C_{2} \\cos{\\left (3 x \\right )} + \\frac{1}{9}$$" ], "text/plain": [ - "f(x) = C\u2081\u22c5sin(3\u22c5x) + C\u2082\u22c5cos(3\u22c5x) + 1/9" + "f(x) = C₁⋅sin(3⋅x) + C₂⋅cos(3⋅x) + 1/9" ] }, "execution_count": 18, @@ -1647,7 +1647,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Terminal Usage.ipynb b/examples/IPython Kernel/Terminal Usage.ipynb index e01e038..13be327 100644 --- a/examples/IPython Kernel/Terminal Usage.ipynb +++ b/examples/IPython Kernel/Terminal Usage.ipynb @@ -261,7 +261,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Third Party Rich Output.ipynb b/examples/IPython Kernel/Third Party Rich Output.ipynb index a025bb3..776f915 100644 --- a/examples/IPython Kernel/Third Party Rich Output.ipynb +++ b/examples/IPython Kernel/Third Party Rich Output.ipynb @@ -195,7 +195,7 @@ " \n", " \n", "\n", - "

6 rows \u00d7 7 columns

\n", + "

6 rows × 7 columns

\n", "" ], "text/plain": [ @@ -274,9 +274,9 @@ "$$\\frac{3 \\pi}{2} + \\frac{e^{i x}}{x^{2} + y}$$" ], "text/plain": [ - " \u2148\u22c5x \n", - "3\u22c5\u03c0 \u212f \n", - "\u2500\u2500\u2500 + \u2500\u2500\u2500\u2500\u2500\u2500\n", + " ⅈ⋅x \n", + "3⋅π ℯ \n", + "─── + ──────\n", " 2 2 \n", " x + y" ] @@ -303,8 +303,8 @@ "$$\\frac{1}{x} \\left(x \\sin{\\left (x \\right )} - 1\\right) + \\frac{1}{x}$$" ], "text/plain": [ - "x\u22c5sin(x) - 1 1\n", - "\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500 + \u2500\n", + "x⋅sin(x) - 1 1\n", + "──────────── + ─\n", " x x" ] }, @@ -332,8 +332,8 @@ ], "text/plain": [ " 2 4 \n", - " x 5\u22c5x \u239b 6\u239e\n", - "1 + \u2500\u2500 + \u2500\u2500\u2500\u2500 + O\u239dx \u23a0\n", + " x 5⋅x ⎛ 6⎞\n", + "1 + ── + ──── + O⎝x ⎠\n", " 2 24 " ] }, @@ -517,7 +517,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Trapezoid Rule.ipynb b/examples/IPython Kernel/Trapezoid Rule.ipynb index ecdf50c..e6ecd68 100644 --- a/examples/IPython Kernel/Trapezoid Rule.ipynb +++ b/examples/IPython Kernel/Trapezoid Rule.ipynb @@ -384,6 +384,7 @@ "metadata": { "kernelspec": { "display_name": "Python 3", + "language": "python", "name": "python3" }, "language_info": { @@ -401,4 +402,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/IPython Kernel/Working With External Code.ipynb b/examples/IPython Kernel/Working With External Code.ipynb index 6f6c1d2..efad907 100644 --- a/examples/IPython Kernel/Working With External Code.ipynb +++ b/examples/IPython Kernel/Working With External Code.ipynb @@ -333,7 +333,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Index.ipynb b/examples/Index.ipynb index 3e9bc4d..2f71bf0 100644 --- a/examples/Index.ipynb +++ b/examples/Index.ipynb @@ -41,7 +41,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Beat Frequencies.ipynb b/examples/Interactive Widgets/Beat Frequencies.ipynb index 13049a3..1b1cffb 100644 --- a/examples/Interactive Widgets/Beat Frequencies.ipynb +++ b/examples/Interactive Widgets/Beat Frequencies.ipynb @@ -591,7 +591,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Custom Widget - Hello World.ipynb b/examples/Interactive Widgets/Custom Widget - Hello World.ipynb index 8aafc89..e6a5952 100644 --- a/examples/Interactive Widgets/Custom Widget - Hello World.ipynb +++ b/examples/Interactive Widgets/Custom Widget - Hello World.ipynb @@ -769,16 +769,23 @@ ], "metadata": { "kernelspec": { - "codemirror_mode": { - "name": "python", - "version": 2 - }, - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, - "signature": "sha256:608e0df06fe91ef1c013fd236dda33f7ae11019453f72ae446e8ce15bce82eb2" + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Date Picker Widget.ipynb b/examples/Interactive Widgets/Date Picker Widget.ipynb index 5916174..e135653 100644 --- a/examples/Interactive Widgets/Date Picker Widget.ipynb +++ b/examples/Interactive Widgets/Date Picker Widget.ipynb @@ -817,6 +817,7 @@ ], "kernelspec": { "display_name": "Python 3", + "language": "python", "name": "python3" }, "language_info": { diff --git a/examples/Interactive Widgets/Exploring Graphs.ipynb b/examples/Interactive Widgets/Exploring Graphs.ipynb index 74f060d..51b4839 100644 --- a/examples/Interactive Widgets/Exploring Graphs.ipynb +++ b/examples/Interactive Widgets/Exploring Graphs.ipynb @@ -825,12 +825,30 @@ " generator={'lobster': random_lobster,\n", " 'power law': powerlaw_cluster,\n", " 'Newman-Watts-Strogatz': newman_watts_strogatz,\n", - " u'Erd\u0151s-R\u00e9nyi': erdos_renyi,\n", + " u'Erdős-Rényi': erdos_renyi,\n", " });" ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Export As (nbconvert).ipynb b/examples/Interactive Widgets/Export As (nbconvert).ipynb index 9967b18..4ba62ee 100644 --- a/examples/Interactive Widgets/Export As (nbconvert).ipynb +++ b/examples/Interactive Widgets/Export As (nbconvert).ipynb @@ -154,16 +154,23 @@ ], "metadata": { "kernelspec": { - "codemirror_mode": { - "name": "python", - "version": 2 - }, - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, - "signature": "sha256:dc519f61f8a484b3a8f0b05ad1891fad701324c837325b12d31cce4f31647c2f" + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Factoring.ipynb b/examples/Interactive Widgets/Factoring.ipynb index ffab0b5..e7ec59a 100644 --- a/examples/Interactive Widgets/Factoring.ipynb +++ b/examples/Interactive Widgets/Factoring.ipynb @@ -81,8 +81,8 @@ "$$x^{12} - 1 = \\left(x - 1\\right) \\left(x + 1\\right) \\left(x^{2} + 1\\right) \\left(x^{2} - x + 1\\right) \\left(x^{2} + x + 1\\right) \\left(x^{4} - x^{2} + 1\\right)$$" ], "text/plain": [ - " 12 \u239b 2 \u239e \u239b 2 \u239e \u239b 2 \u239e \u239b 4 2 \u239e\n", - "x - 1 = (x - 1)\u22c5(x + 1)\u22c5\u239dx + 1\u23a0\u22c5\u239dx - x + 1\u23a0\u22c5\u239dx + x + 1\u23a0\u22c5\u239dx - x + 1\u23a0" + " 12 ⎛ 2 ⎞ ⎛ 2 ⎞ ⎛ 2 ⎞ ⎛ 4 2 ⎞\n", + "x - 1 = (x - 1)⋅(x + 1)⋅⎝x + 1⎠⋅⎝x - x + 1⎠⋅⎝x + x + 1⎠⋅⎝x - x + 1⎠" ] }, "metadata": {}, @@ -106,11 +106,11 @@ "$$x^{21} - 1 = \\left(x - 1\\right) \\left(x^{2} + x + 1\\right) \\left(x^{6} + x^{5} + x^{4} + x^{3} + x^{2} + x + 1\\right) \\left(x^{12} - x^{11} + x^{9} - x^{8} + x^{6} - x^{4} + x^{3} - x + 1\\right)$$" ], "text/plain": [ - " 21 \u239b 2 \u239e \u239b 6 5 4 3 2 \u239e \u239b 12 11 \n", - "x - 1 = (x - 1)\u22c5\u239dx + x + 1\u23a0\u22c5\u239dx + x + x + x + x + x + 1\u23a0\u22c5\u239dx - x + x\n", + " 21 ⎛ 2 ⎞ ⎛ 6 5 4 3 2 ⎞ ⎛ 12 11 \n", + "x - 1 = (x - 1)⋅⎝x + x + 1⎠⋅⎝x + x + x + x + x + x + 1⎠⋅⎝x - x + x\n", "\n", - "9 8 6 4 3 \u239e\n", - " - x + x - x + x - x + 1\u23a0" + "9 8 6 4 3 ⎞\n", + " - x + x - x + x - x + 1⎠" ] }, "metadata": {}, @@ -131,7 +131,25 @@ "source": [] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/File Upload Widget.ipynb b/examples/Interactive Widgets/File Upload Widget.ipynb index 6ae3a71..283def8 100644 --- a/examples/Interactive Widgets/File Upload Widget.ipynb +++ b/examples/Interactive Widgets/File Upload Widget.ipynb @@ -165,16 +165,23 @@ ] ], "kernelspec": { - "codemirror_mode": { - "name": "python", - "version": 2 - }, - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, - "signature": "sha256:25c43e4f530e049319d587a7e47734cab5b4b4f608f71aa234e821f43076afe8" + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Image Browser.ipynb b/examples/Interactive Widgets/Image Browser.ipynb index 8430f80..1a249ff 100644 --- a/examples/Interactive Widgets/Image Browser.ipynb +++ b/examples/Interactive Widgets/Image Browser.ipynb @@ -297,7 +297,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Image Processing.ipynb b/examples/Interactive Widgets/Image Processing.ipynb index cfa1e10..b6f30b2 100644 --- a/examples/Interactive Widgets/Image Processing.ipynb +++ b/examples/Interactive Widgets/Image Processing.ipynb @@ -26762,7 +26762,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Index.ipynb b/examples/Interactive Widgets/Index.ipynb index 55df639..5049b4f 100644 --- a/examples/Interactive Widgets/Index.ipynb +++ b/examples/Interactive Widgets/Index.ipynb @@ -86,16 +86,23 @@ ], "metadata": { "kernelspec": { - "codemirror_mode": { - "name": "python", - "version": 2 - }, - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, - "signature": "sha256:8e469f292b096d750dc8eeb71caa8c08b26bc722708314a26a7684c380ccd20f" + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Lorenz Differential Equations.ipynb b/examples/Interactive Widgets/Lorenz Differential Equations.ipynb index 1a3deca..950b1ff 100644 --- a/examples/Interactive Widgets/Lorenz Differential Equations.ipynb +++ b/examples/Interactive Widgets/Lorenz Differential Equations.ipynb @@ -13432,6 +13432,7 @@ "metadata": { "kernelspec": { "display_name": "Python 3", + "language": "python", "name": "python3" }, "language_info": { diff --git a/examples/Interactive Widgets/Nonblocking Console.ipynb b/examples/Interactive Widgets/Nonblocking Console.ipynb index 46a9701..2b2be58 100644 --- a/examples/Interactive Widgets/Nonblocking Console.ipynb +++ b/examples/Interactive Widgets/Nonblocking Console.ipynb @@ -217,16 +217,23 @@ ], "metadata": { "kernelspec": { - "codemirror_mode": { - "name": "python", - "version": 2 - }, - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, - "signature": "sha256:3dfbc0dcb1fefc9ef028022760916b0300e14f71bf8e27589e61800841d5839c" + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Using Interact.ipynb b/examples/Interactive Widgets/Using Interact.ipynb index 3b4b5de..17359b2 100644 --- a/examples/Interactive Widgets/Using Interact.ipynb +++ b/examples/Interactive Widgets/Using Interact.ipynb @@ -606,16 +606,23 @@ ], "metadata": { "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, - "display_name": "IPython (Python 3)", - "language": "python", - "name": "python3" - }, - "signature": "sha256:1bbd16f32ec50ec64d4dd646cd6868aeace8091cac989107f2026fc688ca3701" + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Variable Inspector.ipynb b/examples/Interactive Widgets/Variable Inspector.ipynb index fa14c43..34036f2 100644 --- a/examples/Interactive Widgets/Variable Inspector.ipynb +++ b/examples/Interactive Widgets/Variable Inspector.ipynb @@ -218,22 +218,23 @@ ], "metadata": { "kernelspec": { - "display_name": "IPython (Python 2)", - "name": "python2" + "display_name": "Python 3", + "language": "python", + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" + "pygments_lexer": "ipython3", + "version": "3.4.2" } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Widget Basics.ipynb b/examples/Interactive Widgets/Widget Basics.ipynb index f4e56e0..0c10bf3 100644 --- a/examples/Interactive Widgets/Widget Basics.ipynb +++ b/examples/Interactive Widgets/Widget Basics.ipynb @@ -423,16 +423,23 @@ ], "metadata": { "kernelspec": { - "codemirror_mode": { - "name": "python", - "version": 2 - }, - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, - "signature": "sha256:c8af7f5d30b29ee52fe6a79cf0d573c9c2d5b2f522b04731249e3208671741d3" + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Widget Events.ipynb b/examples/Interactive Widgets/Widget Events.ipynb index 75cd86d..27b69f1 100644 --- a/examples/Interactive Widgets/Widget Events.ipynb +++ b/examples/Interactive Widgets/Widget Events.ipynb @@ -361,23 +361,23 @@ ] ], "kernelspec": { - "display_name": "Python 2", - "name": "python2" + "display_name": "Python 3", + "language": "python", + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.8" - }, - "signature": "sha256:b6eadc174d0d9c1907518d9f37760eb3dca3aec0ef1f3746e6f0537a36e99919" + "pygments_lexer": "ipython3", + "version": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Interactive Widgets/Widget List.ipynb b/examples/Interactive Widgets/Widget List.ipynb index ef91fbc..2335868 100644 --- a/examples/Interactive Widgets/Widget List.ipynb +++ b/examples/Interactive Widgets/Widget List.ipynb @@ -565,20 +565,21 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", - "name": "python2" + "display_name": "Python 3", + "language": "python", + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.8" + "pygments_lexer": "ipython3", + "version": "3.4.2" } }, "nbformat": 4, diff --git a/examples/Interactive Widgets/Widget Styling.ipynb b/examples/Interactive Widgets/Widget Styling.ipynb index 5f69fdd..f30f1b0 100644 --- a/examples/Interactive Widgets/Widget Styling.ipynb +++ b/examples/Interactive Widgets/Widget Styling.ipynb @@ -563,22 +563,23 @@ ] ], "kernelspec": { - "display_name": "IPython (Python 2)", - "name": "python2" + "display_name": "Python 3", + "language": "python", + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" + "pygments_lexer": "ipython3", + "version": "3.4.2" } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Connecting with the Qt Console.ipynb b/examples/Notebook/Connecting with the Qt Console.ipynb index c76348b..407f65f 100644 --- a/examples/Notebook/Connecting with the Qt Console.ipynb +++ b/examples/Notebook/Connecting with the Qt Console.ipynb @@ -131,7 +131,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Converting Notebooks With nbconvert.ipynb b/examples/Notebook/Converting Notebooks With nbconvert.ipynb index e9a73b3..d12ed17 100644 --- a/examples/Notebook/Converting Notebooks With nbconvert.ipynb +++ b/examples/Notebook/Converting Notebooks With nbconvert.ipynb @@ -479,7 +479,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Custom Keyboard Shortcuts.ipynb b/examples/Notebook/Custom Keyboard Shortcuts.ipynb index 6cb38ce..7162e2b 100644 --- a/examples/Notebook/Custom Keyboard Shortcuts.ipynb +++ b/examples/Notebook/Custom Keyboard Shortcuts.ipynb @@ -141,7 +141,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Importing Notebooks.ipynb b/examples/Notebook/Importing Notebooks.ipynb index a58e94c..ed1fe70 100644 --- a/examples/Notebook/Importing Notebooks.ipynb +++ b/examples/Notebook/Importing Notebooks.ipynb @@ -710,8 +710,24 @@ ], "metadata": { "gist_id": "6011986", - "signature": "sha256:26d4e13b833b84557da8501e68fc5119f11a3c1cdbecba63c0ab613e0cb0619f" + "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": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Index.ipynb b/examples/Notebook/Index.ipynb index 6d47cd5..4a35e51 100644 --- a/examples/Notebook/Index.ipynb +++ b/examples/Notebook/Index.ipynb @@ -68,7 +68,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/JavaScript Notebook Extensions.ipynb b/examples/Notebook/JavaScript Notebook Extensions.ipynb index b7b8ed3..9fd02cc 100644 --- a/examples/Notebook/JavaScript Notebook Extensions.ipynb +++ b/examples/Notebook/JavaScript Notebook Extensions.ipynb @@ -749,7 +749,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Notebook Basics.ipynb b/examples/Notebook/Notebook Basics.ipynb index ff28b01..ce5c433 100644 --- a/examples/Notebook/Notebook Basics.ipynb +++ b/examples/Notebook/Notebook Basics.ipynb @@ -234,16 +234,23 @@ ], "metadata": { "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, - "display_name": "IPython (Python 3)", - "language": "python", - "name": "python3" - }, - "signature": "sha256:6e4f35a8bc2cb1408b995bc3c006369dd3c3e31a3e6212088f3d1e2abef36407" + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Notebook Security.ipynb b/examples/Notebook/Notebook Security.ipynb index 1084e08..adbb4f9 100644 --- a/examples/Notebook/Notebook Security.ipynb +++ b/examples/Notebook/Notebook Security.ipynb @@ -1,6 +1,24 @@ { "cells": [], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Running Code.ipynb b/examples/Notebook/Running Code.ipynb index b0926dd..e86cfaf 100644 --- a/examples/Notebook/Running Code.ipynb +++ b/examples/Notebook/Running Code.ipynb @@ -870,16 +870,23 @@ ], "metadata": { "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, - "display_name": "IPython (Python 3)", - "language": "python", - "name": "python3" - }, - "signature": "sha256:55c4f2c75812ec42ca18dcd7e895a056a3faa0e6d567893faf8c85345016be06" + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Running the Notebook Server.ipynb b/examples/Notebook/Running the Notebook Server.ipynb index 2a29326..ae235d5 100644 --- a/examples/Notebook/Running the Notebook Server.ipynb +++ b/examples/Notebook/Running the Notebook Server.ipynb @@ -355,7 +355,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Typesetting Equations.ipynb b/examples/Notebook/Typesetting Equations.ipynb index df729bd..77e7909 100644 --- a/examples/Notebook/Typesetting Equations.ipynb +++ b/examples/Notebook/Typesetting Equations.ipynb @@ -247,7 +247,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Using nbconvert as a Library.ipynb b/examples/Notebook/Using nbconvert as a Library.ipynb index 63b3601..ca10728 100644 --- a/examples/Notebook/Using nbconvert as a Library.ipynb +++ b/examples/Notebook/Using nbconvert as a Library.ipynb @@ -1428,6 +1428,7 @@ "metadata": { "kernelspec": { "display_name": "Python 3", + "language": "python", "name": "python3" }, "language_info": { @@ -1445,4 +1446,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/What is the IPython Notebook.ipynb b/examples/Notebook/What is the IPython Notebook.ipynb index f957098..e870879 100644 --- a/examples/Notebook/What is the IPython Notebook.ipynb +++ b/examples/Notebook/What is the IPython Notebook.ipynb @@ -161,8 +161,24 @@ ], "metadata": { "celltoolbar": "Slideshow", - "signature": "sha256:86e99da10fb4a123108149196f182861fa434fb59520b256405c6052601c2486" + "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": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/Working With Markdown Cells.ipynb b/examples/Notebook/Working With Markdown Cells.ipynb index 9bc4b52..4f1c557 100644 --- a/examples/Notebook/Working With Markdown Cells.ipynb +++ b/examples/Notebook/Working With Markdown Cells.ipynb @@ -296,7 +296,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/nbpackage/mynotebook.ipynb b/examples/Notebook/nbpackage/mynotebook.ipynb index daf9299..fd3920c 100644 --- a/examples/Notebook/nbpackage/mynotebook.ipynb +++ b/examples/Notebook/nbpackage/mynotebook.ipynb @@ -45,7 +45,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Notebook/nbpackage/nbs/other.ipynb b/examples/Notebook/nbpackage/nbs/other.ipynb index 5db9938..dad7e73 100644 --- a/examples/Notebook/nbpackage/nbs/other.ipynb +++ b/examples/Notebook/nbpackage/nbs/other.ipynb @@ -20,7 +20,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Parallel Computing/Data Publication API.ipynb b/examples/Parallel Computing/Data Publication API.ipynb index 46ec906..f6077a5 100644 --- a/examples/Parallel Computing/Data Publication API.ipynb +++ b/examples/Parallel Computing/Data Publication API.ipynb @@ -2647,7 +2647,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Parallel Computing/Index.ipynb b/examples/Parallel Computing/Index.ipynb index d6e4fd8..ad56fb9 100644 --- a/examples/Parallel Computing/Index.ipynb +++ b/examples/Parallel Computing/Index.ipynb @@ -328,7 +328,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Parallel Computing/Monitoring an MPI Simulation - 1.ipynb b/examples/Parallel Computing/Monitoring an MPI Simulation - 1.ipynb index 2fdd029..2bfb190 100644 --- a/examples/Parallel Computing/Monitoring an MPI Simulation - 1.ipynb +++ b/examples/Parallel Computing/Monitoring an MPI Simulation - 1.ipynb @@ -860,7 +860,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Parallel Computing/Monitoring an MPI Simulation - 2.ipynb b/examples/Parallel Computing/Monitoring an MPI Simulation - 2.ipynb index 915a903..7f82c42 100644 --- a/examples/Parallel Computing/Monitoring an MPI Simulation - 2.ipynb +++ b/examples/Parallel Computing/Monitoring an MPI Simulation - 2.ipynb @@ -509,7 +509,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Parallel Computing/Monte Carlo Options.ipynb b/examples/Parallel Computing/Monte Carlo Options.ipynb index bd4665a..9c7af67 100644 --- a/examples/Parallel Computing/Monte Carlo Options.ipynb +++ b/examples/Parallel Computing/Monte Carlo Options.ipynb @@ -2533,7 +2533,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Parallel Computing/Parallel Decorator and map.ipynb b/examples/Parallel Computing/Parallel Decorator and map.ipynb index 45097d6..6118bdb 100644 --- a/examples/Parallel Computing/Parallel Decorator and map.ipynb +++ b/examples/Parallel Computing/Parallel Decorator and map.ipynb @@ -107,7 +107,25 @@ "source": [] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Parallel Computing/Parallel Magics.ipynb b/examples/Parallel Computing/Parallel Magics.ipynb index 09474ef..60596e2 100644 --- a/examples/Parallel Computing/Parallel Magics.ipynb +++ b/examples/Parallel Computing/Parallel Magics.ipynb @@ -497,7 +497,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Parallel Computing/Using Dill.ipynb b/examples/Parallel Computing/Using Dill.ipynb index 7615a25..a63554b 100644 --- a/examples/Parallel Computing/Using Dill.ipynb +++ b/examples/Parallel Computing/Using Dill.ipynb @@ -535,8 +535,25 @@ } ], "metadata": { - "gist_id": "5241793" + "gist_id": "5241793", + "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": "3.4.2" + } }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Parallel Computing/Using MPI with IPython Parallel.ipynb b/examples/Parallel Computing/Using MPI with IPython Parallel.ipynb index 7ef3538..2188831 100644 --- a/examples/Parallel Computing/Using MPI with IPython Parallel.ipynb +++ b/examples/Parallel Computing/Using MPI with IPython Parallel.ipynb @@ -182,7 +182,25 @@ "source": [] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/examples/Parallel Computing/rmt/rmt.ipynb b/examples/Parallel Computing/rmt/rmt.ipynb index d646850..abcd453 100644 --- a/examples/Parallel Computing/rmt/rmt.ipynb +++ b/examples/Parallel Computing/rmt/rmt.ipynb @@ -797,7 +797,25 @@ ] } ], - "metadata": {}, + "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": "3.4.2" + } + }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/tools/tests/ANSI Test.ipynb b/tools/tests/ANSI Test.ipynb index 1aa398f..98c91ff 100644 --- a/tools/tests/ANSI Test.ipynb +++ b/tools/tests/ANSI Test.ipynb @@ -1,554 +1,560 @@ { - "metadata": { - "name": "" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ + "cells": [ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This notebook tests the processing of ANSI and VT100 color escapes" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "from __future__ import print_function" - ], - "language": "python", - "metadata": {}, - "outputs": [], - "prompt_number": 5 - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "ESC = '\\x1b['\n", - "RESET = ESC + \"00m\"" - ], - "language": "python", - "metadata": {}, - "outputs": [], - "prompt_number": 41 - }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook tests the processing of ANSI and VT100 color escapes" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "from __future__ import print_function" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "ESC = '\\x1b['\n", + "RESET = ESC + \"00m\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Plain ANSI 16-color" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Plain ANSI 16-color" + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[01;40;30mtext \u001b[01m\u001b[01;40;31mtext \u001b[01m\u001b[01;40;32mtext \u001b[01m\u001b[01;40;33mtext \u001b[01m\u001b[01;40;34mtext \u001b[01m\u001b[01;40;35mtext \u001b[01m\u001b[01;40;36mtext \u001b[01m\u001b[01;40;37mtext \u001b[01m\n", + "\u001b[01;41;30mtext \u001b[01m\u001b[01;41;31mtext \u001b[01m\u001b[01;41;32mtext \u001b[01m\u001b[01;41;33mtext \u001b[01m\u001b[01;41;34mtext \u001b[01m\u001b[01;41;35mtext \u001b[01m\u001b[01;41;36mtext \u001b[01m\u001b[01;41;37mtext \u001b[01m\n", + 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9 - }, + } + ], + "source": [ + "for bg in range(40,48):\n", + " for fg in range(30,38):\n", + " print (\"{ESC}01;{bg};{fg}mtext {RESET}\".format(**locals()), end='')\n", + " print ()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 256-color" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "collapsed": false + }, + "outputs": [ { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "256-color" + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[00;38;5;0m000 \u001b[01m\u001b[00;38;5;1m001 \u001b[01m\u001b[00;38;5;2m002 \u001b[01m\u001b[00;38;5;3m003 \u001b[01m\u001b[00;38;5;4m004 \u001b[01m\u001b[00;38;5;5m005 \u001b[01m\u001b[00;38;5;6m006 \u001b[01m\u001b[00;38;5;7m007 \u001b[01m\n", + "\u001b[00;38;5;8m008 \u001b[01m\u001b[00;38;5;9m009 \u001b[01m\u001b[00;38;5;10m010 \u001b[01m\u001b[00;38;5;11m011 \u001b[01m\u001b[00;38;5;12m012 \u001b[01m\u001b[00;38;5;13m013 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()\n", - "print ()" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\u001b[00;38;5;0m000 \u001b[01m\u001b[00;38;5;1m001 \u001b[01m\u001b[00;38;5;2m002 \u001b[01m\u001b[00;38;5;3m003 \u001b[01m\u001b[00;38;5;4m004 \u001b[01m\u001b[00;38;5;5m005 \u001b[01m\u001b[00;38;5;6m006 \u001b[01m\u001b[00;38;5;7m007 \u001b[01m\n", - "\u001b[00;38;5;8m008 \u001b[01m\u001b[00;38;5;9m009 \u001b[01m\u001b[00;38;5;10m010 \u001b[01m\u001b[00;38;5;11m011 \u001b[01m\u001b[00;38;5;12m012 \u001b[01m\u001b[00;38;5;13m013 \u001b[01m\u001b[00;38;5;14m014 \u001b[01m\u001b[00;38;5;15m015 \u001b[01m\n", - "\n", - "\u001b[00;38;5;16m016 \u001b[01m\u001b[00;38;5;17m017 \u001b[01m\u001b[00;38;5;18m018 \u001b[01m\u001b[00;38;5;19m019 \u001b[01m\u001b[00;38;5;20m020 \u001b[01m\u001b[00;38;5;21m021 \u001b[01m\n", - "\u001b[00;38;5;22m022 \u001b[01m\u001b[00;38;5;23m023 \u001b[01m\u001b[00;38;5;24m024 \u001b[01m\u001b[00;38;5;25m025 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"prompt_number": 27 - }, + } + ], + "source": [ + "t = \"{ESC}00;38;5;{i}m{i:03} {RESET}\"\n", + "for i in range(16):\n", + " print (t.format(**locals()), end='')\n", + " if i % 8 == 7:\n", + " print ()\n", + "print ()\n", + "\n", + "for i in range(16,232):\n", + " print (t.format(**locals()), end='')\n", + " if (i-16) % 6 == 5:\n", + " print ()\n", + " if (i-16) % 36 == 35:\n", + " print ()\n", + "\n", + "print ()\n", + "\n", + "for i in range(232,256):\n", + " print (t.format(**locals()), end='')\n", + " if (i-232) % 12 == 11:\n", + " print ()\n", + "print ()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 256-color background" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false + }, + "outputs": [ { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "256-color background" + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[00;48;5;0m000 \u001b[01m\u001b[00;48;5;1m001 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"\u001b[00;48;5;232m232 \u001b[01m\u001b[00;48;5;233m233 \u001b[01m\u001b[00;48;5;234m234 \u001b[01m\u001b[00;48;5;235m235 \u001b[01m\u001b[00;48;5;236m236 \u001b[01m\u001b[00;48;5;237m237 \u001b[01m\u001b[00;48;5;238m238 \u001b[01m\u001b[00;48;5;239m239 \u001b[01m\u001b[00;48;5;240m240 \u001b[01m\u001b[00;48;5;241m241 \u001b[01m\u001b[00;48;5;242m242 \u001b[01m\u001b[00;48;5;243m243 \u001b[01m\n", + "\u001b[00;48;5;244m244 \u001b[01m\u001b[00;48;5;245m245 \u001b[01m\u001b[00;48;5;246m246 \u001b[01m\u001b[00;48;5;247m247 \u001b[01m\u001b[00;48;5;248m248 \u001b[01m\u001b[00;48;5;249m249 \u001b[01m\u001b[00;48;5;250m250 \u001b[01m\u001b[00;48;5;251m251 \u001b[01m\u001b[00;48;5;252m252 \u001b[01m\u001b[00;48;5;253m253 \u001b[01m\u001b[00;48;5;254m254 \u001b[01m\u001b[00;48;5;255m255 \u001b[01m\n", + "\n" ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "t = \"{ESC}00;48;5;{i}m{i:03} {RESET}\"\n", - "for i in range(16):\n", - " print (t.format(**locals()), end='')\n", - " if i % 8 == 7:\n", - " print ()\n", - "\n", - "print ()\n", - "\n", - "for i in range(16,232):\n", - " print (t.format(**locals()), end='')\n", - " if (i-16) % 6 == 5:\n", - " print ()\n", - " if (i-16) % 36 == 35:\n", - " print ()\n", - "\n", - "print ()\n", - "\n", - "for i in range(232,256):\n", - " print (t.format(**locals()), end='')\n", - " if (i-232) % 12 == 11:\n", - " print ()\n", - "print ()" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\u001b[00;48;5;0m000 \u001b[01m\u001b[00;48;5;1m001 \u001b[01m\u001b[00;48;5;2m002 \u001b[01m\u001b[00;48;5;3m003 \u001b[01m\u001b[00;48;5;4m004 \u001b[01m\u001b[00;48;5;5m005 \u001b[01m\u001b[00;48;5;6m006 \u001b[01m\u001b[00;48;5;7m007 \u001b[01m\n", - "\u001b[00;48;5;8m008 \u001b[01m\u001b[00;48;5;9m009 \u001b[01m\u001b[00;48;5;10m010 \u001b[01m\u001b[00;48;5;11m011 \u001b[01m\u001b[00;48;5;12m012 \u001b[01m\u001b[00;48;5;13m013 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\u001b[01m\n", - "\u001b[00;48;5;244m244 \u001b[01m\u001b[00;48;5;245m245 \u001b[01m\u001b[00;48;5;246m246 \u001b[01m\u001b[00;48;5;247m247 \u001b[01m\u001b[00;48;5;248m248 \u001b[01m\u001b[00;48;5;249m249 \u001b[01m\u001b[00;48;5;250m250 \u001b[01m\u001b[00;48;5;251m251 \u001b[01m\u001b[00;48;5;252m252 \u001b[01m\u001b[00;48;5;253m253 \u001b[01m\u001b[00;48;5;254m254 \u001b[01m\u001b[00;48;5;255m255 \u001b[01m\n", - "\n" - ] - } - ], - "prompt_number": 29 - }, + } + ], + "source": [ + "t = \"{ESC}00;48;5;{i}m{i:03} {RESET}\"\n", + "for i in range(16):\n", + " print (t.format(**locals()), end='')\n", + " if i % 8 == 7:\n", + " print ()\n", + "\n", + "print ()\n", + "\n", + "for i in range(16,232):\n", + " print (t.format(**locals()), end='')\n", + " if (i-16) % 6 == 5:\n", + " print ()\n", + " if (i-16) % 36 == 35:\n", + " print ()\n", + "\n", + "print ()\n", + "\n", + "for i in range(232,256):\n", + " print (t.format(**locals()), end='')\n", + " if (i-232) % 12 == 11:\n", + " print ()\n", + "print ()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 256-color background and foreground" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "collapsed": false + }, + "outputs": [ { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "256-color background and foreground" + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[00;48;5;2;38;5;165m165 on 002 \u001b[00m\u001b[00;48;5;2;38;5;102m102 on 002 \u001b[00m\u001b[00;48;5;2;38;5;252m252 on 002 \u001b[00m\u001b[00;48;5;2;38;5;9m009 on 002 \u001b[00m\n", + "\u001b[00;48;5;57;38;5;165m165 on 057 \u001b[00m\u001b[00;48;5;57;38;5;102m102 on 057 \u001b[00m\u001b[00;48;5;57;38;5;252m252 on 057 \u001b[00m\u001b[00;48;5;57;38;5;9m009 on 057 \u001b[00m\n", + "\u001b[00;48;5;160;38;5;165m165 on 160 \u001b[00m\u001b[00;48;5;160;38;5;102m102 on 160 \u001b[00m\u001b[00;48;5;160;38;5;252m252 on 160 \u001b[00m\u001b[00;48;5;160;38;5;9m009 on 160 \u001b[00m\n", + "\u001b[00;48;5;246;38;5;165m165 on 246 \u001b[00m\u001b[00;48;5;246;38;5;102m102 on 246 \u001b[00m\u001b[00;48;5;246;38;5;252m252 on 246 \u001b[00m\u001b[00;48;5;246;38;5;9m009 on 246 \u001b[00m\n" ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "t = \"{ESC}00;48;5;{bg};38;5;{fg}m{fg:03} on {bg:03} {RESET}\"\n", - "\n", - "for bg in [2, 57, 160, 246]:\n", - " for fg in [165, 102, 252, 9]:\n", - " print (t.format(**locals()), end='')\n", - " print()\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\u001b[00;48;5;2;38;5;165m165 on 002 \u001b[00m\u001b[00;48;5;2;38;5;102m102 on 002 \u001b[00m\u001b[00;48;5;2;38;5;252m252 on 002 \u001b[00m\u001b[00;48;5;2;38;5;9m009 on 002 \u001b[00m\n", - "\u001b[00;48;5;57;38;5;165m165 on 057 \u001b[00m\u001b[00;48;5;57;38;5;102m102 on 057 \u001b[00m\u001b[00;48;5;57;38;5;252m252 on 057 \u001b[00m\u001b[00;48;5;57;38;5;9m009 on 057 \u001b[00m\n", - "\u001b[00;48;5;160;38;5;165m165 on 160 \u001b[00m\u001b[00;48;5;160;38;5;102m102 on 160 \u001b[00m\u001b[00;48;5;160;38;5;252m252 on 160 \u001b[00m\u001b[00;48;5;160;38;5;9m009 on 160 \u001b[00m\n", - "\u001b[00;48;5;246;38;5;165m165 on 246 \u001b[00m\u001b[00;48;5;246;38;5;102m102 on 246 \u001b[00m\u001b[00;48;5;246;38;5;252m252 on 246 \u001b[00m\u001b[00;48;5;246;38;5;9m009 on 246 \u001b[00m\n" - ] - } - ], - "prompt_number": 42 - }, + } + ], + "source": [ + "t = \"{ESC}00;48;5;{bg};38;5;{fg}m{fg:03} on {bg:03} {RESET}\"\n", + "\n", + "for bg in [2, 57, 160, 246]:\n", + " for fg in [165, 102, 252, 9]:\n", + " print (t.format(**locals()), end='')\n", + " print()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 24-bit RGB" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "collapsed": false + }, + "outputs": [ { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "24-bit RGB" + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[00;38;2;0;0;0m000|000|000 \u001b[00m\u001b[00;38;2;0;0;30m000|000|030 \u001b[00m\u001b[00;38;2;0;0;60m000|000|060 \u001b[00m\u001b[00;38;2;0;0;90m000|000|090 \u001b[00m\u001b[00;38;2;0;0;120m000|000|120 \u001b[00m\u001b[00;38;2;0;0;150m000|000|150 \u001b[00m\u001b[00;38;2;0;0;180m000|000|180 \u001b[00m\u001b[00;38;2;0;0;210m000|000|210 \u001b[00m\u001b[00;38;2;0;0;240m000|000|240 \u001b[00m\n", + "\u001b[00;38;2;0;30;0m000|030|000 \u001b[00m\u001b[00;38;2;0;30;30m000|030|030 \u001b[00m\u001b[00;38;2;0;30;60m000|030|060 \u001b[00m\u001b[00;38;2;0;30;90m000|030|090 \u001b[00m\u001b[00;38;2;0;30;120m000|030|120 \u001b[00m\u001b[00;38;2;0;30;150m000|030|150 \u001b[00m\u001b[00;38;2;0;30;180m000|030|180 \u001b[00m\u001b[00;38;2;0;30;210m000|030|210 \u001b[00m\u001b[00;38;2;0;30;240m000|030|240 \u001b[00m\n", + "\u001b[00;38;2;0;60;0m000|060|000 \u001b[00m\u001b[00;38;2;0;60;30m000|060|030 \u001b[00m\u001b[00;38;2;0;60;60m000|060|060 \u001b[00m\u001b[00;38;2;0;60;90m000|060|090 \u001b[00m\u001b[00;38;2;0;60;120m000|060|120 \u001b[00m\u001b[00;38;2;0;60;150m000|060|150 \u001b[00m\u001b[00;38;2;0;60;180m000|060|180 \u001b[00m\u001b[00;38;2;0;60;210m000|060|210 \u001b[00m\u001b[00;38;2;0;60;240m000|060|240 \u001b[00m\n", + "\u001b[00;38;2;0;90;0m000|090|000 \u001b[00m\u001b[00;38;2;0;90;30m000|090|030 \u001b[00m\u001b[00;38;2;0;90;60m000|090|060 \u001b[00m\u001b[00;38;2;0;90;90m000|090|090 \u001b[00m\u001b[00;38;2;0;90;120m000|090|120 \u001b[00m\u001b[00;38;2;0;90;150m000|090|150 \u001b[00m\u001b[00;38;2;0;90;180m000|090|180 \u001b[00m\u001b[00;38;2;0;90;210m000|090|210 \u001b[00m\u001b[00;38;2;0;90;240m000|090|240 \u001b[00m\n", + "\u001b[00;38;2;0;120;0m000|120|000 \u001b[00m\u001b[00;38;2;0;120;30m000|120|030 \u001b[00m\u001b[00;38;2;0;120;60m000|120|060 \u001b[00m\u001b[00;38;2;0;120;90m000|120|090 \u001b[00m\u001b[00;38;2;0;120;120m000|120|120 \u001b[00m\u001b[00;38;2;0;120;150m000|120|150 \u001b[00m\u001b[00;38;2;0;120;180m000|120|180 \u001b[00m\u001b[00;38;2;0;120;210m000|120|210 \u001b[00m\u001b[00;38;2;0;120;240m000|120|240 \u001b[00m\n", + "\u001b[00;38;2;0;150;0m000|150|000 \u001b[00m\u001b[00;38;2;0;150;30m000|150|030 \u001b[00m\u001b[00;38;2;0;150;60m000|150|060 \u001b[00m\u001b[00;38;2;0;150;90m000|150|090 \u001b[00m\u001b[00;38;2;0;150;120m000|150|120 \u001b[00m\u001b[00;38;2;0;150;150m000|150|150 \u001b[00m\u001b[00;38;2;0;150;180m000|150|180 \u001b[00m\u001b[00;38;2;0;150;210m000|150|210 \u001b[00m\u001b[00;38;2;0;150;240m000|150|240 \u001b[00m\n", + "\u001b[00;38;2;0;180;0m000|180|000 \u001b[00m\u001b[00;38;2;0;180;30m000|180|030 \u001b[00m\u001b[00;38;2;0;180;60m000|180|060 \u001b[00m\u001b[00;38;2;0;180;90m000|180|090 \u001b[00m\u001b[00;38;2;0;180;120m000|180|120 \u001b[00m\u001b[00;38;2;0;180;150m000|180|150 \u001b[00m\u001b[00;38;2;0;180;180m000|180|180 \u001b[00m\u001b[00;38;2;0;180;210m000|180|210 \u001b[00m\u001b[00;38;2;0;180;240m000|180|240 \u001b[00m\n", + "\u001b[00;38;2;0;210;0m000|210|000 \u001b[00m\u001b[00;38;2;0;210;30m000|210|030 \u001b[00m\u001b[00;38;2;0;210;60m000|210|060 \u001b[00m\u001b[00;38;2;0;210;90m000|210|090 \u001b[00m\u001b[00;38;2;0;210;120m000|210|120 \u001b[00m\u001b[00;38;2;0;210;150m000|210|150 \u001b[00m\u001b[00;38;2;0;210;180m000|210|180 \u001b[00m\u001b[00;38;2;0;210;210m000|210|210 \u001b[00m\u001b[00;38;2;0;210;240m000|210|240 \u001b[00m\n", + "\u001b[00;38;2;0;240;0m000|240|000 \u001b[00m\u001b[00;38;2;0;240;30m000|240|030 \u001b[00m\u001b[00;38;2;0;240;60m000|240|060 \u001b[00m\u001b[00;38;2;0;240;90m000|240|090 \u001b[00m\u001b[00;38;2;0;240;120m000|240|120 \u001b[00m\u001b[00;38;2;0;240;150m000|240|150 \u001b[00m\u001b[00;38;2;0;240;180m000|240|180 \u001b[00m\u001b[00;38;2;0;240;210m000|240|210 \u001b[00m\u001b[00;38;2;0;240;240m000|240|240 \u001b[00m\n", + "\n", + "\u001b[00;38;2;30;0;0m030|000|000 \u001b[00m\u001b[00;38;2;30;0;30m030|000|030 \u001b[00m\u001b[00;38;2;30;0;60m030|000|060 \u001b[00m\u001b[00;38;2;30;0;90m030|000|090 \u001b[00m\u001b[00;38;2;30;0;120m030|000|120 \u001b[00m\u001b[00;38;2;30;0;150m030|000|150 \u001b[00m\u001b[00;38;2;30;0;180m030|000|180 \u001b[00m\u001b[00;38;2;30;0;210m030|000|210 \u001b[00m\u001b[00;38;2;30;0;240m030|000|240 \u001b[00m\n", + "\u001b[00;38;2;30;30;0m030|030|000 \u001b[00m\u001b[00;38;2;30;30;30m030|030|030 \u001b[00m\u001b[00;38;2;30;30;60m030|030|060 \u001b[00m\u001b[00;38;2;30;30;90m030|030|090 \u001b[00m\u001b[00;38;2;30;30;120m030|030|120 \u001b[00m\u001b[00;38;2;30;30;150m030|030|150 \u001b[00m\u001b[00;38;2;30;30;180m030|030|180 \u001b[00m\u001b[00;38;2;30;30;210m030|030|210 \u001b[00m\u001b[00;38;2;30;30;240m030|030|240 \u001b[00m\n", + "\u001b[00;38;2;30;60;0m030|060|000 \u001b[00m\u001b[00;38;2;30;60;30m030|060|030 \u001b[00m\u001b[00;38;2;30;60;60m030|060|060 \u001b[00m\u001b[00;38;2;30;60;90m030|060|090 \u001b[00m\u001b[00;38;2;30;60;120m030|060|120 \u001b[00m\u001b[00;38;2;30;60;150m030|060|150 \u001b[00m\u001b[00;38;2;30;60;180m030|060|180 \u001b[00m\u001b[00;38;2;30;60;210m030|060|210 \u001b[00m\u001b[00;38;2;30;60;240m030|060|240 \u001b[00m\n", + "\u001b[00;38;2;30;90;0m030|090|000 \u001b[00m\u001b[00;38;2;30;90;30m030|090|030 \u001b[00m\u001b[00;38;2;30;90;60m030|090|060 \u001b[00m\u001b[00;38;2;30;90;90m030|090|090 \u001b[00m\u001b[00;38;2;30;90;120m030|090|120 \u001b[00m\u001b[00;38;2;30;90;150m030|090|150 \u001b[00m\u001b[00;38;2;30;90;180m030|090|180 \u001b[00m\u001b[00;38;2;30;90;210m030|090|210 \u001b[00m\u001b[00;38;2;30;90;240m030|090|240 \u001b[00m\n", + "\u001b[00;38;2;30;120;0m030|120|000 \u001b[00m\u001b[00;38;2;30;120;30m030|120|030 \u001b[00m\u001b[00;38;2;30;120;60m030|120|060 \u001b[00m\u001b[00;38;2;30;120;90m030|120|090 \u001b[00m\u001b[00;38;2;30;120;120m030|120|120 \u001b[00m\u001b[00;38;2;30;120;150m030|120|150 \u001b[00m\u001b[00;38;2;30;120;180m030|120|180 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"\u001b[00;38;2;30;210;0m030|210|000 \u001b[00m\u001b[00;38;2;30;210;30m030|210|030 \u001b[00m\u001b[00;38;2;30;210;60m030|210|060 \u001b[00m\u001b[00;38;2;30;210;90m030|210|090 \u001b[00m\u001b[00;38;2;30;210;120m030|210|120 \u001b[00m\u001b[00;38;2;30;210;150m030|210|150 \u001b[00m\u001b[00;38;2;30;210;180m030|210|180 \u001b[00m\u001b[00;38;2;30;210;210m030|210|210 \u001b[00m\u001b[00;38;2;30;210;240m030|210|240 \u001b[00m\n", + "\u001b[00;38;2;30;240;0m030|240|000 \u001b[00m\u001b[00;38;2;30;240;30m030|240|030 \u001b[00m\u001b[00;38;2;30;240;60m030|240|060 \u001b[00m\u001b[00;38;2;30;240;90m030|240|090 \u001b[00m\u001b[00;38;2;30;240;120m030|240|120 \u001b[00m\u001b[00;38;2;30;240;150m030|240|150 \u001b[00m\u001b[00;38;2;30;240;180m030|240|180 \u001b[00m\u001b[00;38;2;30;240;210m030|240|210 \u001b[00m\u001b[00;38;2;30;240;240m030|240|240 \u001b[00m\n", + "\n", + "\u001b[00;38;2;60;0;0m060|000|000 \u001b[00m\u001b[00;38;2;60;0;30m060|000|030 \u001b[00m\u001b[00;38;2;60;0;60m060|000|060 \u001b[00m\u001b[00;38;2;60;0;90m060|000|090 \u001b[00m\u001b[00;38;2;60;0;120m060|000|120 \u001b[00m\u001b[00;38;2;60;0;150m060|000|150 \u001b[00m\u001b[00;38;2;60;0;180m060|000|180 \u001b[00m\u001b[00;38;2;60;0;210m060|000|210 \u001b[00m\u001b[00;38;2;60;0;240m060|000|240 \u001b[00m\n", + "\u001b[00;38;2;60;30;0m060|030|000 \u001b[00m\u001b[00;38;2;60;30;30m060|030|030 \u001b[00m\u001b[00;38;2;60;30;60m060|030|060 \u001b[00m\u001b[00;38;2;60;30;90m060|030|090 \u001b[00m\u001b[00;38;2;60;30;120m060|030|120 \u001b[00m\u001b[00;38;2;60;30;150m060|030|150 \u001b[00m\u001b[00;38;2;60;30;180m060|030|180 \u001b[00m\u001b[00;38;2;60;30;210m060|030|210 \u001b[00m\u001b[00;38;2;60;30;240m060|030|240 \u001b[00m\n", + "\u001b[00;38;2;60;60;0m060|060|000 \u001b[00m\u001b[00;38;2;60;60;30m060|060|030 \u001b[00m\u001b[00;38;2;60;60;60m060|060|060 \u001b[00m\u001b[00;38;2;60;60;90m060|060|090 \u001b[00m\u001b[00;38;2;60;60;120m060|060|120 \u001b[00m\u001b[00;38;2;60;60;150m060|060|150 \u001b[00m\u001b[00;38;2;60;60;180m060|060|180 \u001b[00m\u001b[00;38;2;60;60;210m060|060|210 \u001b[00m\u001b[00;38;2;60;60;240m060|060|240 \u001b[00m\n", + "\u001b[00;38;2;60;90;0m060|090|000 \u001b[00m\u001b[00;38;2;60;90;30m060|090|030 \u001b[00m\u001b[00;38;2;60;90;60m060|090|060 \u001b[00m\u001b[00;38;2;60;90;90m060|090|090 \u001b[00m\u001b[00;38;2;60;90;120m060|090|120 \u001b[00m\u001b[00;38;2;60;90;150m060|090|150 \u001b[00m\u001b[00;38;2;60;90;180m060|090|180 \u001b[00m\u001b[00;38;2;60;90;210m060|090|210 \u001b[00m\u001b[00;38;2;60;90;240m060|090|240 \u001b[00m\n", + "\u001b[00;38;2;60;120;0m060|120|000 \u001b[00m\u001b[00;38;2;60;120;30m060|120|030 \u001b[00m\u001b[00;38;2;60;120;60m060|120|060 \u001b[00m\u001b[00;38;2;60;120;90m060|120|090 \u001b[00m\u001b[00;38;2;60;120;120m060|120|120 \u001b[00m\u001b[00;38;2;60;120;150m060|120|150 \u001b[00m\u001b[00;38;2;60;120;180m060|120|180 \u001b[00m\u001b[00;38;2;60;120;210m060|120|210 \u001b[00m\u001b[00;38;2;60;120;240m060|120|240 \u001b[00m\n", + "\u001b[00;38;2;60;150;0m060|150|000 \u001b[00m\u001b[00;38;2;60;150;30m060|150|030 \u001b[00m\u001b[00;38;2;60;150;60m060|150|060 \u001b[00m\u001b[00;38;2;60;150;90m060|150|090 \u001b[00m\u001b[00;38;2;60;150;120m060|150|120 \u001b[00m\u001b[00;38;2;60;150;150m060|150|150 \u001b[00m\u001b[00;38;2;60;150;180m060|150|180 \u001b[00m\u001b[00;38;2;60;150;210m060|150|210 \u001b[00m\u001b[00;38;2;60;150;240m060|150|240 \u001b[00m\n", + "\u001b[00;38;2;60;180;0m060|180|000 \u001b[00m\u001b[00;38;2;60;180;30m060|180|030 \u001b[00m\u001b[00;38;2;60;180;60m060|180|060 \u001b[00m\u001b[00;38;2;60;180;90m060|180|090 \u001b[00m\u001b[00;38;2;60;180;120m060|180|120 \u001b[00m\u001b[00;38;2;60;180;150m060|180|150 \u001b[00m\u001b[00;38;2;60;180;180m060|180|180 \u001b[00m\u001b[00;38;2;60;180;210m060|180|210 \u001b[00m\u001b[00;38;2;60;180;240m060|180|240 \u001b[00m\n", + "\u001b[00;38;2;60;210;0m060|210|000 \u001b[00m\u001b[00;38;2;60;210;30m060|210|030 \u001b[00m\u001b[00;38;2;60;210;60m060|210|060 \u001b[00m\u001b[00;38;2;60;210;90m060|210|090 \u001b[00m\u001b[00;38;2;60;210;120m060|210|120 \u001b[00m\u001b[00;38;2;60;210;150m060|210|150 \u001b[00m\u001b[00;38;2;60;210;180m060|210|180 \u001b[00m\u001b[00;38;2;60;210;210m060|210|210 \u001b[00m\u001b[00;38;2;60;210;240m060|210|240 \u001b[00m\n", + "\u001b[00;38;2;60;240;0m060|240|000 \u001b[00m\u001b[00;38;2;60;240;30m060|240|030 \u001b[00m\u001b[00;38;2;60;240;60m060|240|060 \u001b[00m\u001b[00;38;2;60;240;90m060|240|090 \u001b[00m\u001b[00;38;2;60;240;120m060|240|120 \u001b[00m\u001b[00;38;2;60;240;150m060|240|150 \u001b[00m\u001b[00;38;2;60;240;180m060|240|180 \u001b[00m\u001b[00;38;2;60;240;210m060|240|210 \u001b[00m\u001b[00;38;2;60;240;240m060|240|240 \u001b[00m\n", + "\n", + "\u001b[00;38;2;90;0;0m090|000|000 \u001b[00m\u001b[00;38;2;90;0;30m090|000|030 \u001b[00m\u001b[00;38;2;90;0;60m090|000|060 \u001b[00m\u001b[00;38;2;90;0;90m090|000|090 \u001b[00m\u001b[00;38;2;90;0;120m090|000|120 \u001b[00m\u001b[00;38;2;90;0;150m090|000|150 \u001b[00m\u001b[00;38;2;90;0;180m090|000|180 \u001b[00m\u001b[00;38;2;90;0;210m090|000|210 \u001b[00m\u001b[00;38;2;90;0;240m090|000|240 \u001b[00m\n", + "\u001b[00;38;2;90;30;0m090|030|000 \u001b[00m\u001b[00;38;2;90;30;30m090|030|030 \u001b[00m\u001b[00;38;2;90;30;60m090|030|060 \u001b[00m\u001b[00;38;2;90;30;90m090|030|090 \u001b[00m\u001b[00;38;2;90;30;120m090|030|120 \u001b[00m\u001b[00;38;2;90;30;150m090|030|150 \u001b[00m\u001b[00;38;2;90;30;180m090|030|180 \u001b[00m\u001b[00;38;2;90;30;210m090|030|210 \u001b[00m\u001b[00;38;2;90;30;240m090|030|240 \u001b[00m\n", + "\u001b[00;38;2;90;60;0m090|060|000 \u001b[00m\u001b[00;38;2;90;60;30m090|060|030 \u001b[00m\u001b[00;38;2;90;60;60m090|060|060 \u001b[00m\u001b[00;38;2;90;60;90m090|060|090 \u001b[00m\u001b[00;38;2;90;60;120m090|060|120 \u001b[00m\u001b[00;38;2;90;60;150m090|060|150 \u001b[00m\u001b[00;38;2;90;60;180m090|060|180 \u001b[00m\u001b[00;38;2;90;60;210m090|060|210 \u001b[00m\u001b[00;38;2;90;60;240m090|060|240 \u001b[00m\n", + "\u001b[00;38;2;90;90;0m090|090|000 \u001b[00m\u001b[00;38;2;90;90;30m090|090|030 \u001b[00m\u001b[00;38;2;90;90;60m090|090|060 \u001b[00m\u001b[00;38;2;90;90;90m090|090|090 \u001b[00m\u001b[00;38;2;90;90;120m090|090|120 \u001b[00m\u001b[00;38;2;90;90;150m090|090|150 \u001b[00m\u001b[00;38;2;90;90;180m090|090|180 \u001b[00m\u001b[00;38;2;90;90;210m090|090|210 \u001b[00m\u001b[00;38;2;90;90;240m090|090|240 \u001b[00m\n", + "\u001b[00;38;2;90;120;0m090|120|000 \u001b[00m\u001b[00;38;2;90;120;30m090|120|030 \u001b[00m\u001b[00;38;2;90;120;60m090|120|060 \u001b[00m\u001b[00;38;2;90;120;90m090|120|090 \u001b[00m\u001b[00;38;2;90;120;120m090|120|120 \u001b[00m\u001b[00;38;2;90;120;150m090|120|150 \u001b[00m\u001b[00;38;2;90;120;180m090|120|180 \u001b[00m\u001b[00;38;2;90;120;210m090|120|210 \u001b[00m\u001b[00;38;2;90;120;240m090|120|240 \u001b[00m\n", + "\u001b[00;38;2;90;150;0m090|150|000 \u001b[00m\u001b[00;38;2;90;150;30m090|150|030 \u001b[00m\u001b[00;38;2;90;150;60m090|150|060 \u001b[00m\u001b[00;38;2;90;150;90m090|150|090 \u001b[00m\u001b[00;38;2;90;150;120m090|150|120 \u001b[00m\u001b[00;38;2;90;150;150m090|150|150 \u001b[00m\u001b[00;38;2;90;150;180m090|150|180 \u001b[00m\u001b[00;38;2;90;150;210m090|150|210 \u001b[00m\u001b[00;38;2;90;150;240m090|150|240 \u001b[00m\n", + "\u001b[00;38;2;90;180;0m090|180|000 \u001b[00m\u001b[00;38;2;90;180;30m090|180|030 \u001b[00m\u001b[00;38;2;90;180;60m090|180|060 \u001b[00m\u001b[00;38;2;90;180;90m090|180|090 \u001b[00m\u001b[00;38;2;90;180;120m090|180|120 \u001b[00m\u001b[00;38;2;90;180;150m090|180|150 \u001b[00m\u001b[00;38;2;90;180;180m090|180|180 \u001b[00m\u001b[00;38;2;90;180;210m090|180|210 \u001b[00m\u001b[00;38;2;90;180;240m090|180|240 \u001b[00m\n", + "\u001b[00;38;2;90;210;0m090|210|000 \u001b[00m\u001b[00;38;2;90;210;30m090|210|030 \u001b[00m\u001b[00;38;2;90;210;60m090|210|060 \u001b[00m\u001b[00;38;2;90;210;90m090|210|090 \u001b[00m\u001b[00;38;2;90;210;120m090|210|120 \u001b[00m\u001b[00;38;2;90;210;150m090|210|150 \u001b[00m\u001b[00;38;2;90;210;180m090|210|180 \u001b[00m\u001b[00;38;2;90;210;210m090|210|210 \u001b[00m\u001b[00;38;2;90;210;240m090|210|240 \u001b[00m\n", + "\u001b[00;38;2;90;240;0m090|240|000 \u001b[00m\u001b[00;38;2;90;240;30m090|240|030 \u001b[00m\u001b[00;38;2;90;240;60m090|240|060 \u001b[00m\u001b[00;38;2;90;240;90m090|240|090 \u001b[00m\u001b[00;38;2;90;240;120m090|240|120 \u001b[00m\u001b[00;38;2;90;240;150m090|240|150 \u001b[00m\u001b[00;38;2;90;240;180m090|240|180 \u001b[00m\u001b[00;38;2;90;240;210m090|240|210 \u001b[00m\u001b[00;38;2;90;240;240m090|240|240 \u001b[00m\n", + "\n", + "\u001b[00;38;2;120;0;0m120|000|000 \u001b[00m\u001b[00;38;2;120;0;30m120|000|030 \u001b[00m\u001b[00;38;2;120;0;60m120|000|060 \u001b[00m\u001b[00;38;2;120;0;90m120|000|090 \u001b[00m\u001b[00;38;2;120;0;120m120|000|120 \u001b[00m\u001b[00;38;2;120;0;150m120|000|150 \u001b[00m\u001b[00;38;2;120;0;180m120|000|180 \u001b[00m\u001b[00;38;2;120;0;210m120|000|210 \u001b[00m\u001b[00;38;2;120;0;240m120|000|240 \u001b[00m\n", + "\u001b[00;38;2;120;30;0m120|030|000 \u001b[00m\u001b[00;38;2;120;30;30m120|030|030 \u001b[00m\u001b[00;38;2;120;30;60m120|030|060 \u001b[00m\u001b[00;38;2;120;30;90m120|030|090 \u001b[00m\u001b[00;38;2;120;30;120m120|030|120 \u001b[00m\u001b[00;38;2;120;30;150m120|030|150 \u001b[00m\u001b[00;38;2;120;30;180m120|030|180 \u001b[00m\u001b[00;38;2;120;30;210m120|030|210 \u001b[00m\u001b[00;38;2;120;30;240m120|030|240 \u001b[00m\n", + "\u001b[00;38;2;120;60;0m120|060|000 \u001b[00m\u001b[00;38;2;120;60;30m120|060|030 \u001b[00m\u001b[00;38;2;120;60;60m120|060|060 \u001b[00m\u001b[00;38;2;120;60;90m120|060|090 \u001b[00m\u001b[00;38;2;120;60;120m120|060|120 \u001b[00m\u001b[00;38;2;120;60;150m120|060|150 \u001b[00m\u001b[00;38;2;120;60;180m120|060|180 \u001b[00m\u001b[00;38;2;120;60;210m120|060|210 \u001b[00m\u001b[00;38;2;120;60;240m120|060|240 \u001b[00m\n", + "\u001b[00;38;2;120;90;0m120|090|000 \u001b[00m\u001b[00;38;2;120;90;30m120|090|030 \u001b[00m\u001b[00;38;2;120;90;60m120|090|060 \u001b[00m\u001b[00;38;2;120;90;90m120|090|090 \u001b[00m\u001b[00;38;2;120;90;120m120|090|120 \u001b[00m\u001b[00;38;2;120;90;150m120|090|150 \u001b[00m\u001b[00;38;2;120;90;180m120|090|180 \u001b[00m\u001b[00;38;2;120;90;210m120|090|210 \u001b[00m\u001b[00;38;2;120;90;240m120|090|240 \u001b[00m\n", + "\u001b[00;38;2;120;120;0m120|120|000 \u001b[00m\u001b[00;38;2;120;120;30m120|120|030 \u001b[00m\u001b[00;38;2;120;120;60m120|120|060 \u001b[00m\u001b[00;38;2;120;120;90m120|120|090 \u001b[00m\u001b[00;38;2;120;120;120m120|120|120 \u001b[00m\u001b[00;38;2;120;120;150m120|120|150 \u001b[00m\u001b[00;38;2;120;120;180m120|120|180 \u001b[00m\u001b[00;38;2;120;120;210m120|120|210 \u001b[00m\u001b[00;38;2;120;120;240m120|120|240 \u001b[00m\n", + "\u001b[00;38;2;120;150;0m120|150|000 \u001b[00m\u001b[00;38;2;120;150;30m120|150|030 \u001b[00m\u001b[00;38;2;120;150;60m120|150|060 \u001b[00m\u001b[00;38;2;120;150;90m120|150|090 \u001b[00m\u001b[00;38;2;120;150;120m120|150|120 \u001b[00m\u001b[00;38;2;120;150;150m120|150|150 \u001b[00m\u001b[00;38;2;120;150;180m120|150|180 \u001b[00m\u001b[00;38;2;120;150;210m120|150|210 \u001b[00m\u001b[00;38;2;120;150;240m120|150|240 \u001b[00m\n", + "\u001b[00;38;2;120;180;0m120|180|000 \u001b[00m\u001b[00;38;2;120;180;30m120|180|030 \u001b[00m\u001b[00;38;2;120;180;60m120|180|060 \u001b[00m\u001b[00;38;2;120;180;90m120|180|090 \u001b[00m\u001b[00;38;2;120;180;120m120|180|120 \u001b[00m\u001b[00;38;2;120;180;150m120|180|150 \u001b[00m\u001b[00;38;2;120;180;180m120|180|180 \u001b[00m\u001b[00;38;2;120;180;210m120|180|210 \u001b[00m\u001b[00;38;2;120;180;240m120|180|240 \u001b[00m\n", + "\u001b[00;38;2;120;210;0m120|210|000 \u001b[00m\u001b[00;38;2;120;210;30m120|210|030 \u001b[00m\u001b[00;38;2;120;210;60m120|210|060 \u001b[00m\u001b[00;38;2;120;210;90m120|210|090 \u001b[00m\u001b[00;38;2;120;210;120m120|210|120 \u001b[00m\u001b[00;38;2;120;210;150m120|210|150 \u001b[00m\u001b[00;38;2;120;210;180m120|210|180 \u001b[00m\u001b[00;38;2;120;210;210m120|210|210 \u001b[00m\u001b[00;38;2;120;210;240m120|210|240 \u001b[00m\n", + "\u001b[00;38;2;120;240;0m120|240|000 \u001b[00m\u001b[00;38;2;120;240;30m120|240|030 \u001b[00m\u001b[00;38;2;120;240;60m120|240|060 \u001b[00m\u001b[00;38;2;120;240;90m120|240|090 \u001b[00m\u001b[00;38;2;120;240;120m120|240|120 \u001b[00m\u001b[00;38;2;120;240;150m120|240|150 \u001b[00m\u001b[00;38;2;120;240;180m120|240|180 \u001b[00m\u001b[00;38;2;120;240;210m120|240|210 \u001b[00m\u001b[00;38;2;120;240;240m120|240|240 \u001b[00m\n", + "\n", + "\u001b[00;38;2;150;0;0m150|000|000 \u001b[00m\u001b[00;38;2;150;0;30m150|000|030 \u001b[00m\u001b[00;38;2;150;0;60m150|000|060 \u001b[00m\u001b[00;38;2;150;0;90m150|000|090 \u001b[00m\u001b[00;38;2;150;0;120m150|000|120 \u001b[00m\u001b[00;38;2;150;0;150m150|000|150 \u001b[00m\u001b[00;38;2;150;0;180m150|000|180 \u001b[00m\u001b[00;38;2;150;0;210m150|000|210 \u001b[00m\u001b[00;38;2;150;0;240m150|000|240 \u001b[00m\n", + "\u001b[00;38;2;150;30;0m150|030|000 \u001b[00m\u001b[00;38;2;150;30;30m150|030|030 \u001b[00m\u001b[00;38;2;150;30;60m150|030|060 \u001b[00m\u001b[00;38;2;150;30;90m150|030|090 \u001b[00m\u001b[00;38;2;150;30;120m150|030|120 \u001b[00m\u001b[00;38;2;150;30;150m150|030|150 \u001b[00m\u001b[00;38;2;150;30;180m150|030|180 \u001b[00m\u001b[00;38;2;150;30;210m150|030|210 \u001b[00m\u001b[00;38;2;150;30;240m150|030|240 \u001b[00m\n", + "\u001b[00;38;2;150;60;0m150|060|000 \u001b[00m\u001b[00;38;2;150;60;30m150|060|030 \u001b[00m\u001b[00;38;2;150;60;60m150|060|060 \u001b[00m\u001b[00;38;2;150;60;90m150|060|090 \u001b[00m\u001b[00;38;2;150;60;120m150|060|120 \u001b[00m\u001b[00;38;2;150;60;150m150|060|150 \u001b[00m\u001b[00;38;2;150;60;180m150|060|180 \u001b[00m\u001b[00;38;2;150;60;210m150|060|210 \u001b[00m\u001b[00;38;2;150;60;240m150|060|240 \u001b[00m\n", + "\u001b[00;38;2;150;90;0m150|090|000 \u001b[00m\u001b[00;38;2;150;90;30m150|090|030 \u001b[00m\u001b[00;38;2;150;90;60m150|090|060 \u001b[00m\u001b[00;38;2;150;90;90m150|090|090 \u001b[00m\u001b[00;38;2;150;90;120m150|090|120 \u001b[00m\u001b[00;38;2;150;90;150m150|090|150 \u001b[00m\u001b[00;38;2;150;90;180m150|090|180 \u001b[00m\u001b[00;38;2;150;90;210m150|090|210 \u001b[00m\u001b[00;38;2;150;90;240m150|090|240 \u001b[00m\n", + "\u001b[00;38;2;150;120;0m150|120|000 \u001b[00m\u001b[00;38;2;150;120;30m150|120|030 \u001b[00m\u001b[00;38;2;150;120;60m150|120|060 \u001b[00m\u001b[00;38;2;150;120;90m150|120|090 \u001b[00m\u001b[00;38;2;150;120;120m150|120|120 \u001b[00m\u001b[00;38;2;150;120;150m150|120|150 \u001b[00m\u001b[00;38;2;150;120;180m150|120|180 \u001b[00m\u001b[00;38;2;150;120;210m150|120|210 \u001b[00m\u001b[00;38;2;150;120;240m150|120|240 \u001b[00m\n", + "\u001b[00;38;2;150;150;0m150|150|000 \u001b[00m\u001b[00;38;2;150;150;30m150|150|030 \u001b[00m\u001b[00;38;2;150;150;60m150|150|060 \u001b[00m\u001b[00;38;2;150;150;90m150|150|090 \u001b[00m\u001b[00;38;2;150;150;120m150|150|120 \u001b[00m\u001b[00;38;2;150;150;150m150|150|150 \u001b[00m\u001b[00;38;2;150;150;180m150|150|180 \u001b[00m\u001b[00;38;2;150;150;210m150|150|210 \u001b[00m\u001b[00;38;2;150;150;240m150|150|240 \u001b[00m\n", + "\u001b[00;38;2;150;180;0m150|180|000 \u001b[00m\u001b[00;38;2;150;180;30m150|180|030 \u001b[00m\u001b[00;38;2;150;180;60m150|180|060 \u001b[00m\u001b[00;38;2;150;180;90m150|180|090 \u001b[00m\u001b[00;38;2;150;180;120m150|180|120 \u001b[00m\u001b[00;38;2;150;180;150m150|180|150 \u001b[00m\u001b[00;38;2;150;180;180m150|180|180 \u001b[00m\u001b[00;38;2;150;180;210m150|180|210 \u001b[00m\u001b[00;38;2;150;180;240m150|180|240 \u001b[00m\n", + "\u001b[00;38;2;150;210;0m150|210|000 \u001b[00m\u001b[00;38;2;150;210;30m150|210|030 \u001b[00m\u001b[00;38;2;150;210;60m150|210|060 \u001b[00m\u001b[00;38;2;150;210;90m150|210|090 \u001b[00m\u001b[00;38;2;150;210;120m150|210|120 \u001b[00m\u001b[00;38;2;150;210;150m150|210|150 \u001b[00m\u001b[00;38;2;150;210;180m150|210|180 \u001b[00m\u001b[00;38;2;150;210;210m150|210|210 \u001b[00m\u001b[00;38;2;150;210;240m150|210|240 \u001b[00m\n", + "\u001b[00;38;2;150;240;0m150|240|000 \u001b[00m\u001b[00;38;2;150;240;30m150|240|030 \u001b[00m\u001b[00;38;2;150;240;60m150|240|060 \u001b[00m\u001b[00;38;2;150;240;90m150|240|090 \u001b[00m\u001b[00;38;2;150;240;120m150|240|120 \u001b[00m\u001b[00;38;2;150;240;150m150|240|150 \u001b[00m\u001b[00;38;2;150;240;180m150|240|180 \u001b[00m\u001b[00;38;2;150;240;210m150|240|210 \u001b[00m\u001b[00;38;2;150;240;240m150|240|240 \u001b[00m\n", + "\n", + "\u001b[00;38;2;180;0;0m180|000|000 \u001b[00m\u001b[00;38;2;180;0;30m180|000|030 \u001b[00m\u001b[00;38;2;180;0;60m180|000|060 \u001b[00m\u001b[00;38;2;180;0;90m180|000|090 \u001b[00m\u001b[00;38;2;180;0;120m180|000|120 \u001b[00m\u001b[00;38;2;180;0;150m180|000|150 \u001b[00m\u001b[00;38;2;180;0;180m180|000|180 \u001b[00m\u001b[00;38;2;180;0;210m180|000|210 \u001b[00m\u001b[00;38;2;180;0;240m180|000|240 \u001b[00m\n", + "\u001b[00;38;2;180;30;0m180|030|000 \u001b[00m\u001b[00;38;2;180;30;30m180|030|030 \u001b[00m\u001b[00;38;2;180;30;60m180|030|060 \u001b[00m\u001b[00;38;2;180;30;90m180|030|090 \u001b[00m\u001b[00;38;2;180;30;120m180|030|120 \u001b[00m\u001b[00;38;2;180;30;150m180|030|150 \u001b[00m\u001b[00;38;2;180;30;180m180|030|180 \u001b[00m\u001b[00;38;2;180;30;210m180|030|210 \u001b[00m\u001b[00;38;2;180;30;240m180|030|240 \u001b[00m\n", + "\u001b[00;38;2;180;60;0m180|060|000 \u001b[00m\u001b[00;38;2;180;60;30m180|060|030 \u001b[00m\u001b[00;38;2;180;60;60m180|060|060 \u001b[00m\u001b[00;38;2;180;60;90m180|060|090 \u001b[00m\u001b[00;38;2;180;60;120m180|060|120 \u001b[00m\u001b[00;38;2;180;60;150m180|060|150 \u001b[00m\u001b[00;38;2;180;60;180m180|060|180 \u001b[00m\u001b[00;38;2;180;60;210m180|060|210 \u001b[00m\u001b[00;38;2;180;60;240m180|060|240 \u001b[00m\n", + "\u001b[00;38;2;180;90;0m180|090|000 \u001b[00m\u001b[00;38;2;180;90;30m180|090|030 \u001b[00m\u001b[00;38;2;180;90;60m180|090|060 \u001b[00m\u001b[00;38;2;180;90;90m180|090|090 \u001b[00m\u001b[00;38;2;180;90;120m180|090|120 \u001b[00m\u001b[00;38;2;180;90;150m180|090|150 \u001b[00m\u001b[00;38;2;180;90;180m180|090|180 \u001b[00m\u001b[00;38;2;180;90;210m180|090|210 \u001b[00m\u001b[00;38;2;180;90;240m180|090|240 \u001b[00m\n", + "\u001b[00;38;2;180;120;0m180|120|000 \u001b[00m\u001b[00;38;2;180;120;30m180|120|030 \u001b[00m\u001b[00;38;2;180;120;60m180|120|060 \u001b[00m\u001b[00;38;2;180;120;90m180|120|090 \u001b[00m\u001b[00;38;2;180;120;120m180|120|120 \u001b[00m\u001b[00;38;2;180;120;150m180|120|150 \u001b[00m\u001b[00;38;2;180;120;180m180|120|180 \u001b[00m\u001b[00;38;2;180;120;210m180|120|210 \u001b[00m\u001b[00;38;2;180;120;240m180|120|240 \u001b[00m\n", + "\u001b[00;38;2;180;150;0m180|150|000 \u001b[00m\u001b[00;38;2;180;150;30m180|150|030 \u001b[00m\u001b[00;38;2;180;150;60m180|150|060 \u001b[00m\u001b[00;38;2;180;150;90m180|150|090 \u001b[00m\u001b[00;38;2;180;150;120m180|150|120 \u001b[00m\u001b[00;38;2;180;150;150m180|150|150 \u001b[00m\u001b[00;38;2;180;150;180m180|150|180 \u001b[00m\u001b[00;38;2;180;150;210m180|150|210 \u001b[00m\u001b[00;38;2;180;150;240m180|150|240 \u001b[00m\n", + "\u001b[00;38;2;180;180;0m180|180|000 \u001b[00m\u001b[00;38;2;180;180;30m180|180|030 \u001b[00m\u001b[00;38;2;180;180;60m180|180|060 \u001b[00m\u001b[00;38;2;180;180;90m180|180|090 \u001b[00m\u001b[00;38;2;180;180;120m180|180|120 \u001b[00m\u001b[00;38;2;180;180;150m180|180|150 \u001b[00m\u001b[00;38;2;180;180;180m180|180|180 \u001b[00m\u001b[00;38;2;180;180;210m180|180|210 \u001b[00m\u001b[00;38;2;180;180;240m180|180|240 \u001b[00m\n", + "\u001b[00;38;2;180;210;0m180|210|000 \u001b[00m\u001b[00;38;2;180;210;30m180|210|030 \u001b[00m\u001b[00;38;2;180;210;60m180|210|060 \u001b[00m\u001b[00;38;2;180;210;90m180|210|090 \u001b[00m\u001b[00;38;2;180;210;120m180|210|120 \u001b[00m\u001b[00;38;2;180;210;150m180|210|150 \u001b[00m\u001b[00;38;2;180;210;180m180|210|180 \u001b[00m\u001b[00;38;2;180;210;210m180|210|210 \u001b[00m\u001b[00;38;2;180;210;240m180|210|240 \u001b[00m\n", + "\u001b[00;38;2;180;240;0m180|240|000 \u001b[00m\u001b[00;38;2;180;240;30m180|240|030 \u001b[00m\u001b[00;38;2;180;240;60m180|240|060 \u001b[00m\u001b[00;38;2;180;240;90m180|240|090 \u001b[00m\u001b[00;38;2;180;240;120m180|240|120 \u001b[00m\u001b[00;38;2;180;240;150m180|240|150 \u001b[00m\u001b[00;38;2;180;240;180m180|240|180 \u001b[00m\u001b[00;38;2;180;240;210m180|240|210 \u001b[00m\u001b[00;38;2;180;240;240m180|240|240 \u001b[00m\n", + "\n", + "\u001b[00;38;2;210;0;0m210|000|000 \u001b[00m\u001b[00;38;2;210;0;30m210|000|030 \u001b[00m\u001b[00;38;2;210;0;60m210|000|060 \u001b[00m\u001b[00;38;2;210;0;90m210|000|090 \u001b[00m\u001b[00;38;2;210;0;120m210|000|120 \u001b[00m\u001b[00;38;2;210;0;150m210|000|150 \u001b[00m\u001b[00;38;2;210;0;180m210|000|180 \u001b[00m\u001b[00;38;2;210;0;210m210|000|210 \u001b[00m\u001b[00;38;2;210;0;240m210|000|240 \u001b[00m\n", + "\u001b[00;38;2;210;30;0m210|030|000 \u001b[00m\u001b[00;38;2;210;30;30m210|030|030 \u001b[00m\u001b[00;38;2;210;30;60m210|030|060 \u001b[00m\u001b[00;38;2;210;30;90m210|030|090 \u001b[00m\u001b[00;38;2;210;30;120m210|030|120 \u001b[00m\u001b[00;38;2;210;30;150m210|030|150 \u001b[00m\u001b[00;38;2;210;30;180m210|030|180 \u001b[00m\u001b[00;38;2;210;30;210m210|030|210 \u001b[00m\u001b[00;38;2;210;30;240m210|030|240 \u001b[00m\n", + "\u001b[00;38;2;210;60;0m210|060|000 \u001b[00m\u001b[00;38;2;210;60;30m210|060|030 \u001b[00m\u001b[00;38;2;210;60;60m210|060|060 \u001b[00m\u001b[00;38;2;210;60;90m210|060|090 \u001b[00m\u001b[00;38;2;210;60;120m210|060|120 \u001b[00m\u001b[00;38;2;210;60;150m210|060|150 \u001b[00m\u001b[00;38;2;210;60;180m210|060|180 \u001b[00m\u001b[00;38;2;210;60;210m210|060|210 \u001b[00m\u001b[00;38;2;210;60;240m210|060|240 \u001b[00m\n", + "\u001b[00;38;2;210;90;0m210|090|000 \u001b[00m\u001b[00;38;2;210;90;30m210|090|030 \u001b[00m\u001b[00;38;2;210;90;60m210|090|060 \u001b[00m\u001b[00;38;2;210;90;90m210|090|090 \u001b[00m\u001b[00;38;2;210;90;120m210|090|120 \u001b[00m\u001b[00;38;2;210;90;150m210|090|150 \u001b[00m\u001b[00;38;2;210;90;180m210|090|180 \u001b[00m\u001b[00;38;2;210;90;210m210|090|210 \u001b[00m\u001b[00;38;2;210;90;240m210|090|240 \u001b[00m\n", + "\u001b[00;38;2;210;120;0m210|120|000 \u001b[00m\u001b[00;38;2;210;120;30m210|120|030 \u001b[00m\u001b[00;38;2;210;120;60m210|120|060 \u001b[00m\u001b[00;38;2;210;120;90m210|120|090 \u001b[00m\u001b[00;38;2;210;120;120m210|120|120 \u001b[00m\u001b[00;38;2;210;120;150m210|120|150 \u001b[00m\u001b[00;38;2;210;120;180m210|120|180 \u001b[00m\u001b[00;38;2;210;120;210m210|120|210 \u001b[00m\u001b[00;38;2;210;120;240m210|120|240 \u001b[00m\n", + "\u001b[00;38;2;210;150;0m210|150|000 \u001b[00m\u001b[00;38;2;210;150;30m210|150|030 \u001b[00m\u001b[00;38;2;210;150;60m210|150|060 \u001b[00m\u001b[00;38;2;210;150;90m210|150|090 \u001b[00m\u001b[00;38;2;210;150;120m210|150|120 \u001b[00m\u001b[00;38;2;210;150;150m210|150|150 \u001b[00m\u001b[00;38;2;210;150;180m210|150|180 \u001b[00m\u001b[00;38;2;210;150;210m210|150|210 \u001b[00m\u001b[00;38;2;210;150;240m210|150|240 \u001b[00m\n", + "\u001b[00;38;2;210;180;0m210|180|000 \u001b[00m\u001b[00;38;2;210;180;30m210|180|030 \u001b[00m\u001b[00;38;2;210;180;60m210|180|060 \u001b[00m\u001b[00;38;2;210;180;90m210|180|090 \u001b[00m\u001b[00;38;2;210;180;120m210|180|120 \u001b[00m\u001b[00;38;2;210;180;150m210|180|150 \u001b[00m\u001b[00;38;2;210;180;180m210|180|180 \u001b[00m\u001b[00;38;2;210;180;210m210|180|210 \u001b[00m\u001b[00;38;2;210;180;240m210|180|240 \u001b[00m\n", + "\u001b[00;38;2;210;210;0m210|210|000 \u001b[00m\u001b[00;38;2;210;210;30m210|210|030 \u001b[00m\u001b[00;38;2;210;210;60m210|210|060 \u001b[00m\u001b[00;38;2;210;210;90m210|210|090 \u001b[00m\u001b[00;38;2;210;210;120m210|210|120 \u001b[00m\u001b[00;38;2;210;210;150m210|210|150 \u001b[00m\u001b[00;38;2;210;210;180m210|210|180 \u001b[00m\u001b[00;38;2;210;210;210m210|210|210 \u001b[00m\u001b[00;38;2;210;210;240m210|210|240 \u001b[00m\n", + "\u001b[00;38;2;210;240;0m210|240|000 \u001b[00m\u001b[00;38;2;210;240;30m210|240|030 \u001b[00m\u001b[00;38;2;210;240;60m210|240|060 \u001b[00m\u001b[00;38;2;210;240;90m210|240|090 \u001b[00m\u001b[00;38;2;210;240;120m210|240|120 \u001b[00m\u001b[00;38;2;210;240;150m210|240|150 \u001b[00m\u001b[00;38;2;210;240;180m210|240|180 \u001b[00m\u001b[00;38;2;210;240;210m210|240|210 \u001b[00m\u001b[00;38;2;210;240;240m210|240|240 \u001b[00m\n", + "\n", + "\u001b[00;38;2;240;0;0m240|000|000 \u001b[00m\u001b[00;38;2;240;0;30m240|000|030 \u001b[00m\u001b[00;38;2;240;0;60m240|000|060 \u001b[00m\u001b[00;38;2;240;0;90m240|000|090 \u001b[00m\u001b[00;38;2;240;0;120m240|000|120 \u001b[00m\u001b[00;38;2;240;0;150m240|000|150 \u001b[00m\u001b[00;38;2;240;0;180m240|000|180 \u001b[00m\u001b[00;38;2;240;0;210m240|000|210 \u001b[00m\u001b[00;38;2;240;0;240m240|000|240 \u001b[00m\n", + "\u001b[00;38;2;240;30;0m240|030|000 \u001b[00m\u001b[00;38;2;240;30;30m240|030|030 \u001b[00m\u001b[00;38;2;240;30;60m240|030|060 \u001b[00m\u001b[00;38;2;240;30;90m240|030|090 \u001b[00m\u001b[00;38;2;240;30;120m240|030|120 \u001b[00m\u001b[00;38;2;240;30;150m240|030|150 \u001b[00m\u001b[00;38;2;240;30;180m240|030|180 \u001b[00m\u001b[00;38;2;240;30;210m240|030|210 \u001b[00m\u001b[00;38;2;240;30;240m240|030|240 \u001b[00m\n", + "\u001b[00;38;2;240;60;0m240|060|000 \u001b[00m\u001b[00;38;2;240;60;30m240|060|030 \u001b[00m\u001b[00;38;2;240;60;60m240|060|060 \u001b[00m\u001b[00;38;2;240;60;90m240|060|090 \u001b[00m\u001b[00;38;2;240;60;120m240|060|120 \u001b[00m\u001b[00;38;2;240;60;150m240|060|150 \u001b[00m\u001b[00;38;2;240;60;180m240|060|180 \u001b[00m\u001b[00;38;2;240;60;210m240|060|210 \u001b[00m\u001b[00;38;2;240;60;240m240|060|240 \u001b[00m\n", + "\u001b[00;38;2;240;90;0m240|090|000 \u001b[00m\u001b[00;38;2;240;90;30m240|090|030 \u001b[00m\u001b[00;38;2;240;90;60m240|090|060 \u001b[00m\u001b[00;38;2;240;90;90m240|090|090 \u001b[00m\u001b[00;38;2;240;90;120m240|090|120 \u001b[00m\u001b[00;38;2;240;90;150m240|090|150 \u001b[00m\u001b[00;38;2;240;90;180m240|090|180 \u001b[00m\u001b[00;38;2;240;90;210m240|090|210 \u001b[00m\u001b[00;38;2;240;90;240m240|090|240 \u001b[00m\n", + "\u001b[00;38;2;240;120;0m240|120|000 \u001b[00m\u001b[00;38;2;240;120;30m240|120|030 \u001b[00m\u001b[00;38;2;240;120;60m240|120|060 \u001b[00m\u001b[00;38;2;240;120;90m240|120|090 \u001b[00m\u001b[00;38;2;240;120;120m240|120|120 \u001b[00m\u001b[00;38;2;240;120;150m240|120|150 \u001b[00m\u001b[00;38;2;240;120;180m240|120|180 \u001b[00m\u001b[00;38;2;240;120;210m240|120|210 \u001b[00m\u001b[00;38;2;240;120;240m240|120|240 \u001b[00m\n", + "\u001b[00;38;2;240;150;0m240|150|000 \u001b[00m\u001b[00;38;2;240;150;30m240|150|030 \u001b[00m\u001b[00;38;2;240;150;60m240|150|060 \u001b[00m\u001b[00;38;2;240;150;90m240|150|090 \u001b[00m\u001b[00;38;2;240;150;120m240|150|120 \u001b[00m\u001b[00;38;2;240;150;150m240|150|150 \u001b[00m\u001b[00;38;2;240;150;180m240|150|180 \u001b[00m\u001b[00;38;2;240;150;210m240|150|210 \u001b[00m\u001b[00;38;2;240;150;240m240|150|240 \u001b[00m\n", + "\u001b[00;38;2;240;180;0m240|180|000 \u001b[00m\u001b[00;38;2;240;180;30m240|180|030 \u001b[00m\u001b[00;38;2;240;180;60m240|180|060 \u001b[00m\u001b[00;38;2;240;180;90m240|180|090 \u001b[00m\u001b[00;38;2;240;180;120m240|180|120 \u001b[00m\u001b[00;38;2;240;180;150m240|180|150 \u001b[00m\u001b[00;38;2;240;180;180m240|180|180 \u001b[00m\u001b[00;38;2;240;180;210m240|180|210 \u001b[00m\u001b[00;38;2;240;180;240m240|180|240 \u001b[00m\n", + "\u001b[00;38;2;240;210;0m240|210|000 \u001b[00m\u001b[00;38;2;240;210;30m240|210|030 \u001b[00m\u001b[00;38;2;240;210;60m240|210|060 \u001b[00m\u001b[00;38;2;240;210;90m240|210|090 \u001b[00m\u001b[00;38;2;240;210;120m240|210|120 \u001b[00m\u001b[00;38;2;240;210;150m240|210|150 \u001b[00m\u001b[00;38;2;240;210;180m240|210|180 \u001b[00m\u001b[00;38;2;240;210;210m240|210|210 \u001b[00m\u001b[00;38;2;240;210;240m240|210|240 \u001b[00m\n", + "\u001b[00;38;2;240;240;0m240|240|000 \u001b[00m\u001b[00;38;2;240;240;30m240|240|030 \u001b[00m\u001b[00;38;2;240;240;60m240|240|060 \u001b[00m\u001b[00;38;2;240;240;90m240|240|090 \u001b[00m\u001b[00;38;2;240;240;120m240|240|120 \u001b[00m\u001b[00;38;2;240;240;150m240|240|150 \u001b[00m\u001b[00;38;2;240;240;180m240|240|180 \u001b[00m\u001b[00;38;2;240;240;210m240|240|210 \u001b[00m\u001b[00;38;2;240;240;240m240|240|240 \u001b[00m\n", + "\n" ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "steps = range(0,256,30)\n", - "\n", - "t = \"{ESC}00;38;2;{r};{g};{b}m{r:03}|{g:03}|{b:03} {RESET}\"\n", - "for r in steps:\n", - " for g in steps:\n", - " for b in steps:\n", - " print (t.format(**locals()), end='')\n", - " print()\n", - " print()\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\u001b[00;38;2;0;0;0m000|000|000 \u001b[00m\u001b[00;38;2;0;0;30m000|000|030 \u001b[00m\u001b[00;38;2;0;0;60m000|000|060 \u001b[00m\u001b[00;38;2;0;0;90m000|000|090 \u001b[00m\u001b[00;38;2;0;0;120m000|000|120 \u001b[00m\u001b[00;38;2;0;0;150m000|000|150 \u001b[00m\u001b[00;38;2;0;0;180m000|000|180 \u001b[00m\u001b[00;38;2;0;0;210m000|000|210 \u001b[00m\u001b[00;38;2;0;0;240m000|000|240 \u001b[00m\n", - "\u001b[00;38;2;0;30;0m000|030|000 \u001b[00m\u001b[00;38;2;0;30;30m000|030|030 \u001b[00m\u001b[00;38;2;0;30;60m000|030|060 \u001b[00m\u001b[00;38;2;0;30;90m000|030|090 \u001b[00m\u001b[00;38;2;0;30;120m000|030|120 \u001b[00m\u001b[00;38;2;0;30;150m000|030|150 \u001b[00m\u001b[00;38;2;0;30;180m000|030|180 \u001b[00m\u001b[00;38;2;0;30;210m000|030|210 \u001b[00m\u001b[00;38;2;0;30;240m000|030|240 \u001b[00m\n", - "\u001b[00;38;2;0;60;0m000|060|000 \u001b[00m\u001b[00;38;2;0;60;30m000|060|030 \u001b[00m\u001b[00;38;2;0;60;60m000|060|060 \u001b[00m\u001b[00;38;2;0;60;90m000|060|090 \u001b[00m\u001b[00;38;2;0;60;120m000|060|120 \u001b[00m\u001b[00;38;2;0;60;150m000|060|150 \u001b[00m\u001b[00;38;2;0;60;180m000|060|180 \u001b[00m\u001b[00;38;2;0;60;210m000|060|210 \u001b[00m\u001b[00;38;2;0;60;240m000|060|240 \u001b[00m\n", - "\u001b[00;38;2;0;90;0m000|090|000 \u001b[00m\u001b[00;38;2;0;90;30m000|090|030 \u001b[00m\u001b[00;38;2;0;90;60m000|090|060 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\u001b[00m\u001b[00;38;2;0;150;180m000|150|180 \u001b[00m\u001b[00;38;2;0;150;210m000|150|210 \u001b[00m\u001b[00;38;2;0;150;240m000|150|240 \u001b[00m\n", - "\u001b[00;38;2;0;180;0m000|180|000 \u001b[00m\u001b[00;38;2;0;180;30m000|180|030 \u001b[00m\u001b[00;38;2;0;180;60m000|180|060 \u001b[00m\u001b[00;38;2;0;180;90m000|180|090 \u001b[00m\u001b[00;38;2;0;180;120m000|180|120 \u001b[00m\u001b[00;38;2;0;180;150m000|180|150 \u001b[00m\u001b[00;38;2;0;180;180m000|180|180 \u001b[00m\u001b[00;38;2;0;180;210m000|180|210 \u001b[00m\u001b[00;38;2;0;180;240m000|180|240 \u001b[00m\n", - "\u001b[00;38;2;0;210;0m000|210|000 \u001b[00m\u001b[00;38;2;0;210;30m000|210|030 \u001b[00m\u001b[00;38;2;0;210;60m000|210|060 \u001b[00m\u001b[00;38;2;0;210;90m000|210|090 \u001b[00m\u001b[00;38;2;0;210;120m000|210|120 \u001b[00m\u001b[00;38;2;0;210;150m000|210|150 \u001b[00m\u001b[00;38;2;0;210;180m000|210|180 \u001b[00m\u001b[00;38;2;0;210;210m000|210|210 \u001b[00m\u001b[00;38;2;0;210;240m000|210|240 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\u001b[00m\u001b[00;38;2;30;30;90m030|030|090 \u001b[00m\u001b[00;38;2;30;30;120m030|030|120 \u001b[00m\u001b[00;38;2;30;30;150m030|030|150 \u001b[00m\u001b[00;38;2;30;30;180m030|030|180 \u001b[00m\u001b[00;38;2;30;30;210m030|030|210 \u001b[00m\u001b[00;38;2;30;30;240m030|030|240 \u001b[00m\n", - "\u001b[00;38;2;30;60;0m030|060|000 \u001b[00m\u001b[00;38;2;30;60;30m030|060|030 \u001b[00m\u001b[00;38;2;30;60;60m030|060|060 \u001b[00m\u001b[00;38;2;30;60;90m030|060|090 \u001b[00m\u001b[00;38;2;30;60;120m030|060|120 \u001b[00m\u001b[00;38;2;30;60;150m030|060|150 \u001b[00m\u001b[00;38;2;30;60;180m030|060|180 \u001b[00m\u001b[00;38;2;30;60;210m030|060|210 \u001b[00m\u001b[00;38;2;30;60;240m030|060|240 \u001b[00m\n", - "\u001b[00;38;2;30;90;0m030|090|000 \u001b[00m\u001b[00;38;2;30;90;30m030|090|030 \u001b[00m\u001b[00;38;2;30;90;60m030|090|060 \u001b[00m\u001b[00;38;2;30;90;90m030|090|090 \u001b[00m\u001b[00;38;2;30;90;120m030|090|120 \u001b[00m\u001b[00;38;2;30;90;150m030|090|150 \u001b[00m\u001b[00;38;2;30;90;180m030|090|180 \u001b[00m\u001b[00;38;2;30;90;210m030|090|210 \u001b[00m\u001b[00;38;2;30;90;240m030|090|240 \u001b[00m\n", - "\u001b[00;38;2;30;120;0m030|120|000 \u001b[00m\u001b[00;38;2;30;120;30m030|120|030 \u001b[00m\u001b[00;38;2;30;120;60m030|120|060 \u001b[00m\u001b[00;38;2;30;120;90m030|120|090 \u001b[00m\u001b[00;38;2;30;120;120m030|120|120 \u001b[00m\u001b[00;38;2;30;120;150m030|120|150 \u001b[00m\u001b[00;38;2;30;120;180m030|120|180 \u001b[00m\u001b[00;38;2;30;120;210m030|120|210 \u001b[00m\u001b[00;38;2;30;120;240m030|120|240 \u001b[00m\n", - "\u001b[00;38;2;30;150;0m030|150|000 \u001b[00m\u001b[00;38;2;30;150;30m030|150|030 \u001b[00m\u001b[00;38;2;30;150;60m030|150|060 \u001b[00m\u001b[00;38;2;30;150;90m030|150|090 \u001b[00m\u001b[00;38;2;30;150;120m030|150|120 \u001b[00m\u001b[00;38;2;30;150;150m030|150|150 \u001b[00m\u001b[00;38;2;30;150;180m030|150|180 \u001b[00m\u001b[00;38;2;30;150;210m030|150|210 \u001b[00m\u001b[00;38;2;30;150;240m030|150|240 \u001b[00m\n", - "\u001b[00;38;2;30;180;0m030|180|000 \u001b[00m\u001b[00;38;2;30;180;30m030|180|030 \u001b[00m\u001b[00;38;2;30;180;60m030|180|060 \u001b[00m\u001b[00;38;2;30;180;90m030|180|090 \u001b[00m\u001b[00;38;2;30;180;120m030|180|120 \u001b[00m\u001b[00;38;2;30;180;150m030|180|150 \u001b[00m\u001b[00;38;2;30;180;180m030|180|180 \u001b[00m\u001b[00;38;2;30;180;210m030|180|210 \u001b[00m\u001b[00;38;2;30;180;240m030|180|240 \u001b[00m\n", - "\u001b[00;38;2;30;210;0m030|210|000 \u001b[00m\u001b[00;38;2;30;210;30m030|210|030 \u001b[00m\u001b[00;38;2;30;210;60m030|210|060 \u001b[00m\u001b[00;38;2;30;210;90m030|210|090 \u001b[00m\u001b[00;38;2;30;210;120m030|210|120 \u001b[00m\u001b[00;38;2;30;210;150m030|210|150 \u001b[00m\u001b[00;38;2;30;210;180m030|210|180 \u001b[00m\u001b[00;38;2;30;210;210m030|210|210 \u001b[00m\u001b[00;38;2;30;210;240m030|210|240 \u001b[00m\n", - "\u001b[00;38;2;30;240;0m030|240|000 \u001b[00m\u001b[00;38;2;30;240;30m030|240|030 \u001b[00m\u001b[00;38;2;30;240;60m030|240|060 \u001b[00m\u001b[00;38;2;30;240;90m030|240|090 \u001b[00m\u001b[00;38;2;30;240;120m030|240|120 \u001b[00m\u001b[00;38;2;30;240;150m030|240|150 \u001b[00m\u001b[00;38;2;30;240;180m030|240|180 \u001b[00m\u001b[00;38;2;30;240;210m030|240|210 \u001b[00m\u001b[00;38;2;30;240;240m030|240|240 \u001b[00m\n", - "\n", - "\u001b[00;38;2;60;0;0m060|000|000 \u001b[00m\u001b[00;38;2;60;0;30m060|000|030 \u001b[00m\u001b[00;38;2;60;0;60m060|000|060 \u001b[00m\u001b[00;38;2;60;0;90m060|000|090 \u001b[00m\u001b[00;38;2;60;0;120m060|000|120 \u001b[00m\u001b[00;38;2;60;0;150m060|000|150 \u001b[00m\u001b[00;38;2;60;0;180m060|000|180 \u001b[00m\u001b[00;38;2;60;0;210m060|000|210 \u001b[00m\u001b[00;38;2;60;0;240m060|000|240 \u001b[00m\n", - "\u001b[00;38;2;60;30;0m060|030|000 \u001b[00m\u001b[00;38;2;60;30;30m060|030|030 \u001b[00m\u001b[00;38;2;60;30;60m060|030|060 \u001b[00m\u001b[00;38;2;60;30;90m060|030|090 \u001b[00m\u001b[00;38;2;60;30;120m060|030|120 \u001b[00m\u001b[00;38;2;60;30;150m060|030|150 \u001b[00m\u001b[00;38;2;60;30;180m060|030|180 \u001b[00m\u001b[00;38;2;60;30;210m060|030|210 \u001b[00m\u001b[00;38;2;60;30;240m060|030|240 \u001b[00m\n", - "\u001b[00;38;2;60;60;0m060|060|000 \u001b[00m\u001b[00;38;2;60;60;30m060|060|030 \u001b[00m\u001b[00;38;2;60;60;60m060|060|060 \u001b[00m\u001b[00;38;2;60;60;90m060|060|090 \u001b[00m\u001b[00;38;2;60;60;120m060|060|120 \u001b[00m\u001b[00;38;2;60;60;150m060|060|150 \u001b[00m\u001b[00;38;2;60;60;180m060|060|180 \u001b[00m\u001b[00;38;2;60;60;210m060|060|210 \u001b[00m\u001b[00;38;2;60;60;240m060|060|240 \u001b[00m\n", - "\u001b[00;38;2;60;90;0m060|090|000 \u001b[00m\u001b[00;38;2;60;90;30m060|090|030 \u001b[00m\u001b[00;38;2;60;90;60m060|090|060 \u001b[00m\u001b[00;38;2;60;90;90m060|090|090 \u001b[00m\u001b[00;38;2;60;90;120m060|090|120 \u001b[00m\u001b[00;38;2;60;90;150m060|090|150 \u001b[00m\u001b[00;38;2;60;90;180m060|090|180 \u001b[00m\u001b[00;38;2;60;90;210m060|090|210 \u001b[00m\u001b[00;38;2;60;90;240m060|090|240 \u001b[00m\n", - "\u001b[00;38;2;60;120;0m060|120|000 \u001b[00m\u001b[00;38;2;60;120;30m060|120|030 \u001b[00m\u001b[00;38;2;60;120;60m060|120|060 \u001b[00m\u001b[00;38;2;60;120;90m060|120|090 \u001b[00m\u001b[00;38;2;60;120;120m060|120|120 \u001b[00m\u001b[00;38;2;60;120;150m060|120|150 \u001b[00m\u001b[00;38;2;60;120;180m060|120|180 \u001b[00m\u001b[00;38;2;60;120;210m060|120|210 \u001b[00m\u001b[00;38;2;60;120;240m060|120|240 \u001b[00m\n", - "\u001b[00;38;2;60;150;0m060|150|000 \u001b[00m\u001b[00;38;2;60;150;30m060|150|030 \u001b[00m\u001b[00;38;2;60;150;60m060|150|060 \u001b[00m\u001b[00;38;2;60;150;90m060|150|090 \u001b[00m\u001b[00;38;2;60;150;120m060|150|120 \u001b[00m\u001b[00;38;2;60;150;150m060|150|150 \u001b[00m\u001b[00;38;2;60;150;180m060|150|180 \u001b[00m\u001b[00;38;2;60;150;210m060|150|210 \u001b[00m\u001b[00;38;2;60;150;240m060|150|240 \u001b[00m\n", - "\u001b[00;38;2;60;180;0m060|180|000 \u001b[00m\u001b[00;38;2;60;180;30m060|180|030 \u001b[00m\u001b[00;38;2;60;180;60m060|180|060 \u001b[00m\u001b[00;38;2;60;180;90m060|180|090 \u001b[00m\u001b[00;38;2;60;180;120m060|180|120 \u001b[00m\u001b[00;38;2;60;180;150m060|180|150 \u001b[00m\u001b[00;38;2;60;180;180m060|180|180 \u001b[00m\u001b[00;38;2;60;180;210m060|180|210 \u001b[00m\u001b[00;38;2;60;180;240m060|180|240 \u001b[00m\n", - "\u001b[00;38;2;60;210;0m060|210|000 \u001b[00m\u001b[00;38;2;60;210;30m060|210|030 \u001b[00m\u001b[00;38;2;60;210;60m060|210|060 \u001b[00m\u001b[00;38;2;60;210;90m060|210|090 \u001b[00m\u001b[00;38;2;60;210;120m060|210|120 \u001b[00m\u001b[00;38;2;60;210;150m060|210|150 \u001b[00m\u001b[00;38;2;60;210;180m060|210|180 \u001b[00m\u001b[00;38;2;60;210;210m060|210|210 \u001b[00m\u001b[00;38;2;60;210;240m060|210|240 \u001b[00m\n", - "\u001b[00;38;2;60;240;0m060|240|000 \u001b[00m\u001b[00;38;2;60;240;30m060|240|030 \u001b[00m\u001b[00;38;2;60;240;60m060|240|060 \u001b[00m\u001b[00;38;2;60;240;90m060|240|090 \u001b[00m\u001b[00;38;2;60;240;120m060|240|120 \u001b[00m\u001b[00;38;2;60;240;150m060|240|150 \u001b[00m\u001b[00;38;2;60;240;180m060|240|180 \u001b[00m\u001b[00;38;2;60;240;210m060|240|210 \u001b[00m\u001b[00;38;2;60;240;240m060|240|240 \u001b[00m\n", - "\n", - "\u001b[00;38;2;90;0;0m090|000|000 \u001b[00m\u001b[00;38;2;90;0;30m090|000|030 \u001b[00m\u001b[00;38;2;90;0;60m090|000|060 \u001b[00m\u001b[00;38;2;90;0;90m090|000|090 \u001b[00m\u001b[00;38;2;90;0;120m090|000|120 \u001b[00m\u001b[00;38;2;90;0;150m090|000|150 \u001b[00m\u001b[00;38;2;90;0;180m090|000|180 \u001b[00m\u001b[00;38;2;90;0;210m090|000|210 \u001b[00m\u001b[00;38;2;90;0;240m090|000|240 \u001b[00m\n", - "\u001b[00;38;2;90;30;0m090|030|000 \u001b[00m\u001b[00;38;2;90;30;30m090|030|030 \u001b[00m\u001b[00;38;2;90;30;60m090|030|060 \u001b[00m\u001b[00;38;2;90;30;90m090|030|090 \u001b[00m\u001b[00;38;2;90;30;120m090|030|120 \u001b[00m\u001b[00;38;2;90;30;150m090|030|150 \u001b[00m\u001b[00;38;2;90;30;180m090|030|180 \u001b[00m\u001b[00;38;2;90;30;210m090|030|210 \u001b[00m\u001b[00;38;2;90;30;240m090|030|240 \u001b[00m\n", - "\u001b[00;38;2;90;60;0m090|060|000 \u001b[00m\u001b[00;38;2;90;60;30m090|060|030 \u001b[00m\u001b[00;38;2;90;60;60m090|060|060 \u001b[00m\u001b[00;38;2;90;60;90m090|060|090 \u001b[00m\u001b[00;38;2;90;60;120m090|060|120 \u001b[00m\u001b[00;38;2;90;60;150m090|060|150 \u001b[00m\u001b[00;38;2;90;60;180m090|060|180 \u001b[00m\u001b[00;38;2;90;60;210m090|060|210 \u001b[00m\u001b[00;38;2;90;60;240m090|060|240 \u001b[00m\n", - "\u001b[00;38;2;90;90;0m090|090|000 \u001b[00m\u001b[00;38;2;90;90;30m090|090|030 \u001b[00m\u001b[00;38;2;90;90;60m090|090|060 \u001b[00m\u001b[00;38;2;90;90;90m090|090|090 \u001b[00m\u001b[00;38;2;90;90;120m090|090|120 \u001b[00m\u001b[00;38;2;90;90;150m090|090|150 \u001b[00m\u001b[00;38;2;90;90;180m090|090|180 \u001b[00m\u001b[00;38;2;90;90;210m090|090|210 \u001b[00m\u001b[00;38;2;90;90;240m090|090|240 \u001b[00m\n", - "\u001b[00;38;2;90;120;0m090|120|000 \u001b[00m\u001b[00;38;2;90;120;30m090|120|030 \u001b[00m\u001b[00;38;2;90;120;60m090|120|060 \u001b[00m\u001b[00;38;2;90;120;90m090|120|090 \u001b[00m\u001b[00;38;2;90;120;120m090|120|120 \u001b[00m\u001b[00;38;2;90;120;150m090|120|150 \u001b[00m\u001b[00;38;2;90;120;180m090|120|180 \u001b[00m\u001b[00;38;2;90;120;210m090|120|210 \u001b[00m\u001b[00;38;2;90;120;240m090|120|240 \u001b[00m\n", - "\u001b[00;38;2;90;150;0m090|150|000 \u001b[00m\u001b[00;38;2;90;150;30m090|150|030 \u001b[00m\u001b[00;38;2;90;150;60m090|150|060 \u001b[00m\u001b[00;38;2;90;150;90m090|150|090 \u001b[00m\u001b[00;38;2;90;150;120m090|150|120 \u001b[00m\u001b[00;38;2;90;150;150m090|150|150 \u001b[00m\u001b[00;38;2;90;150;180m090|150|180 \u001b[00m\u001b[00;38;2;90;150;210m090|150|210 \u001b[00m\u001b[00;38;2;90;150;240m090|150|240 \u001b[00m\n", - "\u001b[00;38;2;90;180;0m090|180|000 \u001b[00m\u001b[00;38;2;90;180;30m090|180|030 \u001b[00m\u001b[00;38;2;90;180;60m090|180|060 \u001b[00m\u001b[00;38;2;90;180;90m090|180|090 \u001b[00m\u001b[00;38;2;90;180;120m090|180|120 \u001b[00m\u001b[00;38;2;90;180;150m090|180|150 \u001b[00m\u001b[00;38;2;90;180;180m090|180|180 \u001b[00m\u001b[00;38;2;90;180;210m090|180|210 \u001b[00m\u001b[00;38;2;90;180;240m090|180|240 \u001b[00m\n", - "\u001b[00;38;2;90;210;0m090|210|000 \u001b[00m\u001b[00;38;2;90;210;30m090|210|030 \u001b[00m\u001b[00;38;2;90;210;60m090|210|060 \u001b[00m\u001b[00;38;2;90;210;90m090|210|090 \u001b[00m\u001b[00;38;2;90;210;120m090|210|120 \u001b[00m\u001b[00;38;2;90;210;150m090|210|150 \u001b[00m\u001b[00;38;2;90;210;180m090|210|180 \u001b[00m\u001b[00;38;2;90;210;210m090|210|210 \u001b[00m\u001b[00;38;2;90;210;240m090|210|240 \u001b[00m\n", - "\u001b[00;38;2;90;240;0m090|240|000 \u001b[00m\u001b[00;38;2;90;240;30m090|240|030 \u001b[00m\u001b[00;38;2;90;240;60m090|240|060 \u001b[00m\u001b[00;38;2;90;240;90m090|240|090 \u001b[00m\u001b[00;38;2;90;240;120m090|240|120 \u001b[00m\u001b[00;38;2;90;240;150m090|240|150 \u001b[00m\u001b[00;38;2;90;240;180m090|240|180 \u001b[00m\u001b[00;38;2;90;240;210m090|240|210 \u001b[00m\u001b[00;38;2;90;240;240m090|240|240 \u001b[00m\n", - "\n", - "\u001b[00;38;2;120;0;0m120|000|000 \u001b[00m\u001b[00;38;2;120;0;30m120|000|030 \u001b[00m\u001b[00;38;2;120;0;60m120|000|060 \u001b[00m\u001b[00;38;2;120;0;90m120|000|090 \u001b[00m\u001b[00;38;2;120;0;120m120|000|120 \u001b[00m\u001b[00;38;2;120;0;150m120|000|150 \u001b[00m\u001b[00;38;2;120;0;180m120|000|180 \u001b[00m\u001b[00;38;2;120;0;210m120|000|210 \u001b[00m\u001b[00;38;2;120;0;240m120|000|240 \u001b[00m\n", - "\u001b[00;38;2;120;30;0m120|030|000 \u001b[00m\u001b[00;38;2;120;30;30m120|030|030 \u001b[00m\u001b[00;38;2;120;30;60m120|030|060 \u001b[00m\u001b[00;38;2;120;30;90m120|030|090 \u001b[00m\u001b[00;38;2;120;30;120m120|030|120 \u001b[00m\u001b[00;38;2;120;30;150m120|030|150 \u001b[00m\u001b[00;38;2;120;30;180m120|030|180 \u001b[00m\u001b[00;38;2;120;30;210m120|030|210 \u001b[00m\u001b[00;38;2;120;30;240m120|030|240 \u001b[00m\n", - "\u001b[00;38;2;120;60;0m120|060|000 \u001b[00m\u001b[00;38;2;120;60;30m120|060|030 \u001b[00m\u001b[00;38;2;120;60;60m120|060|060 \u001b[00m\u001b[00;38;2;120;60;90m120|060|090 \u001b[00m\u001b[00;38;2;120;60;120m120|060|120 \u001b[00m\u001b[00;38;2;120;60;150m120|060|150 \u001b[00m\u001b[00;38;2;120;60;180m120|060|180 \u001b[00m\u001b[00;38;2;120;60;210m120|060|210 \u001b[00m\u001b[00;38;2;120;60;240m120|060|240 \u001b[00m\n", - "\u001b[00;38;2;120;90;0m120|090|000 \u001b[00m\u001b[00;38;2;120;90;30m120|090|030 \u001b[00m\u001b[00;38;2;120;90;60m120|090|060 \u001b[00m\u001b[00;38;2;120;90;90m120|090|090 \u001b[00m\u001b[00;38;2;120;90;120m120|090|120 \u001b[00m\u001b[00;38;2;120;90;150m120|090|150 \u001b[00m\u001b[00;38;2;120;90;180m120|090|180 \u001b[00m\u001b[00;38;2;120;90;210m120|090|210 \u001b[00m\u001b[00;38;2;120;90;240m120|090|240 \u001b[00m\n", - "\u001b[00;38;2;120;120;0m120|120|000 \u001b[00m\u001b[00;38;2;120;120;30m120|120|030 \u001b[00m\u001b[00;38;2;120;120;60m120|120|060 \u001b[00m\u001b[00;38;2;120;120;90m120|120|090 \u001b[00m\u001b[00;38;2;120;120;120m120|120|120 \u001b[00m\u001b[00;38;2;120;120;150m120|120|150 \u001b[00m\u001b[00;38;2;120;120;180m120|120|180 \u001b[00m\u001b[00;38;2;120;120;210m120|120|210 \u001b[00m\u001b[00;38;2;120;120;240m120|120|240 \u001b[00m\n", - "\u001b[00;38;2;120;150;0m120|150|000 \u001b[00m\u001b[00;38;2;120;150;30m120|150|030 \u001b[00m\u001b[00;38;2;120;150;60m120|150|060 \u001b[00m\u001b[00;38;2;120;150;90m120|150|090 \u001b[00m\u001b[00;38;2;120;150;120m120|150|120 \u001b[00m\u001b[00;38;2;120;150;150m120|150|150 \u001b[00m\u001b[00;38;2;120;150;180m120|150|180 \u001b[00m\u001b[00;38;2;120;150;210m120|150|210 \u001b[00m\u001b[00;38;2;120;150;240m120|150|240 \u001b[00m\n", - "\u001b[00;38;2;120;180;0m120|180|000 \u001b[00m\u001b[00;38;2;120;180;30m120|180|030 \u001b[00m\u001b[00;38;2;120;180;60m120|180|060 \u001b[00m\u001b[00;38;2;120;180;90m120|180|090 \u001b[00m\u001b[00;38;2;120;180;120m120|180|120 \u001b[00m\u001b[00;38;2;120;180;150m120|180|150 \u001b[00m\u001b[00;38;2;120;180;180m120|180|180 \u001b[00m\u001b[00;38;2;120;180;210m120|180|210 \u001b[00m\u001b[00;38;2;120;180;240m120|180|240 \u001b[00m\n", - "\u001b[00;38;2;120;210;0m120|210|000 \u001b[00m\u001b[00;38;2;120;210;30m120|210|030 \u001b[00m\u001b[00;38;2;120;210;60m120|210|060 \u001b[00m\u001b[00;38;2;120;210;90m120|210|090 \u001b[00m\u001b[00;38;2;120;210;120m120|210|120 \u001b[00m\u001b[00;38;2;120;210;150m120|210|150 \u001b[00m\u001b[00;38;2;120;210;180m120|210|180 \u001b[00m\u001b[00;38;2;120;210;210m120|210|210 \u001b[00m\u001b[00;38;2;120;210;240m120|210|240 \u001b[00m\n", - "\u001b[00;38;2;120;240;0m120|240|000 \u001b[00m\u001b[00;38;2;120;240;30m120|240|030 \u001b[00m\u001b[00;38;2;120;240;60m120|240|060 \u001b[00m\u001b[00;38;2;120;240;90m120|240|090 \u001b[00m\u001b[00;38;2;120;240;120m120|240|120 \u001b[00m\u001b[00;38;2;120;240;150m120|240|150 \u001b[00m\u001b[00;38;2;120;240;180m120|240|180 \u001b[00m\u001b[00;38;2;120;240;210m120|240|210 \u001b[00m\u001b[00;38;2;120;240;240m120|240|240 \u001b[00m\n", - "\n", - "\u001b[00;38;2;150;0;0m150|000|000 \u001b[00m\u001b[00;38;2;150;0;30m150|000|030 \u001b[00m\u001b[00;38;2;150;0;60m150|000|060 \u001b[00m\u001b[00;38;2;150;0;90m150|000|090 \u001b[00m\u001b[00;38;2;150;0;120m150|000|120 \u001b[00m\u001b[00;38;2;150;0;150m150|000|150 \u001b[00m\u001b[00;38;2;150;0;180m150|000|180 \u001b[00m\u001b[00;38;2;150;0;210m150|000|210 \u001b[00m\u001b[00;38;2;150;0;240m150|000|240 \u001b[00m\n", - "\u001b[00;38;2;150;30;0m150|030|000 \u001b[00m\u001b[00;38;2;150;30;30m150|030|030 \u001b[00m\u001b[00;38;2;150;30;60m150|030|060 \u001b[00m\u001b[00;38;2;150;30;90m150|030|090 \u001b[00m\u001b[00;38;2;150;30;120m150|030|120 \u001b[00m\u001b[00;38;2;150;30;150m150|030|150 \u001b[00m\u001b[00;38;2;150;30;180m150|030|180 \u001b[00m\u001b[00;38;2;150;30;210m150|030|210 \u001b[00m\u001b[00;38;2;150;30;240m150|030|240 \u001b[00m\n", - "\u001b[00;38;2;150;60;0m150|060|000 \u001b[00m\u001b[00;38;2;150;60;30m150|060|030 \u001b[00m\u001b[00;38;2;150;60;60m150|060|060 \u001b[00m\u001b[00;38;2;150;60;90m150|060|090 \u001b[00m\u001b[00;38;2;150;60;120m150|060|120 \u001b[00m\u001b[00;38;2;150;60;150m150|060|150 \u001b[00m\u001b[00;38;2;150;60;180m150|060|180 \u001b[00m\u001b[00;38;2;150;60;210m150|060|210 \u001b[00m\u001b[00;38;2;150;60;240m150|060|240 \u001b[00m\n", - "\u001b[00;38;2;150;90;0m150|090|000 \u001b[00m\u001b[00;38;2;150;90;30m150|090|030 \u001b[00m\u001b[00;38;2;150;90;60m150|090|060 \u001b[00m\u001b[00;38;2;150;90;90m150|090|090 \u001b[00m\u001b[00;38;2;150;90;120m150|090|120 \u001b[00m\u001b[00;38;2;150;90;150m150|090|150 \u001b[00m\u001b[00;38;2;150;90;180m150|090|180 \u001b[00m\u001b[00;38;2;150;90;210m150|090|210 \u001b[00m\u001b[00;38;2;150;90;240m150|090|240 \u001b[00m\n", - "\u001b[00;38;2;150;120;0m150|120|000 \u001b[00m\u001b[00;38;2;150;120;30m150|120|030 \u001b[00m\u001b[00;38;2;150;120;60m150|120|060 \u001b[00m\u001b[00;38;2;150;120;90m150|120|090 \u001b[00m\u001b[00;38;2;150;120;120m150|120|120 \u001b[00m\u001b[00;38;2;150;120;150m150|120|150 \u001b[00m\u001b[00;38;2;150;120;180m150|120|180 \u001b[00m\u001b[00;38;2;150;120;210m150|120|210 \u001b[00m\u001b[00;38;2;150;120;240m150|120|240 \u001b[00m\n", - "\u001b[00;38;2;150;150;0m150|150|000 \u001b[00m\u001b[00;38;2;150;150;30m150|150|030 \u001b[00m\u001b[00;38;2;150;150;60m150|150|060 \u001b[00m\u001b[00;38;2;150;150;90m150|150|090 \u001b[00m\u001b[00;38;2;150;150;120m150|150|120 \u001b[00m\u001b[00;38;2;150;150;150m150|150|150 \u001b[00m\u001b[00;38;2;150;150;180m150|150|180 \u001b[00m\u001b[00;38;2;150;150;210m150|150|210 \u001b[00m\u001b[00;38;2;150;150;240m150|150|240 \u001b[00m\n", - "\u001b[00;38;2;150;180;0m150|180|000 \u001b[00m\u001b[00;38;2;150;180;30m150|180|030 \u001b[00m\u001b[00;38;2;150;180;60m150|180|060 \u001b[00m\u001b[00;38;2;150;180;90m150|180|090 \u001b[00m\u001b[00;38;2;150;180;120m150|180|120 \u001b[00m\u001b[00;38;2;150;180;150m150|180|150 \u001b[00m\u001b[00;38;2;150;180;180m150|180|180 \u001b[00m\u001b[00;38;2;150;180;210m150|180|210 \u001b[00m\u001b[00;38;2;150;180;240m150|180|240 \u001b[00m\n", - "\u001b[00;38;2;150;210;0m150|210|000 \u001b[00m\u001b[00;38;2;150;210;30m150|210|030 \u001b[00m\u001b[00;38;2;150;210;60m150|210|060 \u001b[00m\u001b[00;38;2;150;210;90m150|210|090 \u001b[00m\u001b[00;38;2;150;210;120m150|210|120 \u001b[00m\u001b[00;38;2;150;210;150m150|210|150 \u001b[00m\u001b[00;38;2;150;210;180m150|210|180 \u001b[00m\u001b[00;38;2;150;210;210m150|210|210 \u001b[00m\u001b[00;38;2;150;210;240m150|210|240 \u001b[00m\n", - "\u001b[00;38;2;150;240;0m150|240|000 \u001b[00m\u001b[00;38;2;150;240;30m150|240|030 \u001b[00m\u001b[00;38;2;150;240;60m150|240|060 \u001b[00m\u001b[00;38;2;150;240;90m150|240|090 \u001b[00m\u001b[00;38;2;150;240;120m150|240|120 \u001b[00m\u001b[00;38;2;150;240;150m150|240|150 \u001b[00m\u001b[00;38;2;150;240;180m150|240|180 \u001b[00m\u001b[00;38;2;150;240;210m150|240|210 \u001b[00m\u001b[00;38;2;150;240;240m150|240|240 \u001b[00m\n", - "\n", - "\u001b[00;38;2;180;0;0m180|000|000 \u001b[00m\u001b[00;38;2;180;0;30m180|000|030 \u001b[00m\u001b[00;38;2;180;0;60m180|000|060 \u001b[00m\u001b[00;38;2;180;0;90m180|000|090 \u001b[00m\u001b[00;38;2;180;0;120m180|000|120 \u001b[00m\u001b[00;38;2;180;0;150m180|000|150 \u001b[00m\u001b[00;38;2;180;0;180m180|000|180 \u001b[00m\u001b[00;38;2;180;0;210m180|000|210 \u001b[00m\u001b[00;38;2;180;0;240m180|000|240 \u001b[00m\n", - "\u001b[00;38;2;180;30;0m180|030|000 \u001b[00m\u001b[00;38;2;180;30;30m180|030|030 \u001b[00m\u001b[00;38;2;180;30;60m180|030|060 \u001b[00m\u001b[00;38;2;180;30;90m180|030|090 \u001b[00m\u001b[00;38;2;180;30;120m180|030|120 \u001b[00m\u001b[00;38;2;180;30;150m180|030|150 \u001b[00m\u001b[00;38;2;180;30;180m180|030|180 \u001b[00m\u001b[00;38;2;180;30;210m180|030|210 \u001b[00m\u001b[00;38;2;180;30;240m180|030|240 \u001b[00m\n", - "\u001b[00;38;2;180;60;0m180|060|000 \u001b[00m\u001b[00;38;2;180;60;30m180|060|030 \u001b[00m\u001b[00;38;2;180;60;60m180|060|060 \u001b[00m\u001b[00;38;2;180;60;90m180|060|090 \u001b[00m\u001b[00;38;2;180;60;120m180|060|120 \u001b[00m\u001b[00;38;2;180;60;150m180|060|150 \u001b[00m\u001b[00;38;2;180;60;180m180|060|180 \u001b[00m\u001b[00;38;2;180;60;210m180|060|210 \u001b[00m\u001b[00;38;2;180;60;240m180|060|240 \u001b[00m\n", - "\u001b[00;38;2;180;90;0m180|090|000 \u001b[00m\u001b[00;38;2;180;90;30m180|090|030 \u001b[00m\u001b[00;38;2;180;90;60m180|090|060 \u001b[00m\u001b[00;38;2;180;90;90m180|090|090 \u001b[00m\u001b[00;38;2;180;90;120m180|090|120 \u001b[00m\u001b[00;38;2;180;90;150m180|090|150 \u001b[00m\u001b[00;38;2;180;90;180m180|090|180 \u001b[00m\u001b[00;38;2;180;90;210m180|090|210 \u001b[00m\u001b[00;38;2;180;90;240m180|090|240 \u001b[00m\n", - "\u001b[00;38;2;180;120;0m180|120|000 \u001b[00m\u001b[00;38;2;180;120;30m180|120|030 \u001b[00m\u001b[00;38;2;180;120;60m180|120|060 \u001b[00m\u001b[00;38;2;180;120;90m180|120|090 \u001b[00m\u001b[00;38;2;180;120;120m180|120|120 \u001b[00m\u001b[00;38;2;180;120;150m180|120|150 \u001b[00m\u001b[00;38;2;180;120;180m180|120|180 \u001b[00m\u001b[00;38;2;180;120;210m180|120|210 \u001b[00m\u001b[00;38;2;180;120;240m180|120|240 \u001b[00m\n", - "\u001b[00;38;2;180;150;0m180|150|000 \u001b[00m\u001b[00;38;2;180;150;30m180|150|030 \u001b[00m\u001b[00;38;2;180;150;60m180|150|060 \u001b[00m\u001b[00;38;2;180;150;90m180|150|090 \u001b[00m\u001b[00;38;2;180;150;120m180|150|120 \u001b[00m\u001b[00;38;2;180;150;150m180|150|150 \u001b[00m\u001b[00;38;2;180;150;180m180|150|180 \u001b[00m\u001b[00;38;2;180;150;210m180|150|210 \u001b[00m\u001b[00;38;2;180;150;240m180|150|240 \u001b[00m\n", - "\u001b[00;38;2;180;180;0m180|180|000 \u001b[00m\u001b[00;38;2;180;180;30m180|180|030 \u001b[00m\u001b[00;38;2;180;180;60m180|180|060 \u001b[00m\u001b[00;38;2;180;180;90m180|180|090 \u001b[00m\u001b[00;38;2;180;180;120m180|180|120 \u001b[00m\u001b[00;38;2;180;180;150m180|180|150 \u001b[00m\u001b[00;38;2;180;180;180m180|180|180 \u001b[00m\u001b[00;38;2;180;180;210m180|180|210 \u001b[00m\u001b[00;38;2;180;180;240m180|180|240 \u001b[00m\n", - "\u001b[00;38;2;180;210;0m180|210|000 \u001b[00m\u001b[00;38;2;180;210;30m180|210|030 \u001b[00m\u001b[00;38;2;180;210;60m180|210|060 \u001b[00m\u001b[00;38;2;180;210;90m180|210|090 \u001b[00m\u001b[00;38;2;180;210;120m180|210|120 \u001b[00m\u001b[00;38;2;180;210;150m180|210|150 \u001b[00m\u001b[00;38;2;180;210;180m180|210|180 \u001b[00m\u001b[00;38;2;180;210;210m180|210|210 \u001b[00m\u001b[00;38;2;180;210;240m180|210|240 \u001b[00m\n", - "\u001b[00;38;2;180;240;0m180|240|000 \u001b[00m\u001b[00;38;2;180;240;30m180|240|030 \u001b[00m\u001b[00;38;2;180;240;60m180|240|060 \u001b[00m\u001b[00;38;2;180;240;90m180|240|090 \u001b[00m\u001b[00;38;2;180;240;120m180|240|120 \u001b[00m\u001b[00;38;2;180;240;150m180|240|150 \u001b[00m\u001b[00;38;2;180;240;180m180|240|180 \u001b[00m\u001b[00;38;2;180;240;210m180|240|210 \u001b[00m\u001b[00;38;2;180;240;240m180|240|240 \u001b[00m\n", - "\n", - "\u001b[00;38;2;210;0;0m210|000|000 \u001b[00m\u001b[00;38;2;210;0;30m210|000|030 \u001b[00m\u001b[00;38;2;210;0;60m210|000|060 \u001b[00m\u001b[00;38;2;210;0;90m210|000|090 \u001b[00m\u001b[00;38;2;210;0;120m210|000|120 \u001b[00m\u001b[00;38;2;210;0;150m210|000|150 \u001b[00m\u001b[00;38;2;210;0;180m210|000|180 \u001b[00m\u001b[00;38;2;210;0;210m210|000|210 \u001b[00m\u001b[00;38;2;210;0;240m210|000|240 \u001b[00m\n", - "\u001b[00;38;2;210;30;0m210|030|000 \u001b[00m\u001b[00;38;2;210;30;30m210|030|030 \u001b[00m\u001b[00;38;2;210;30;60m210|030|060 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"metadata": { + "collapsed": false + }, + "outputs": [ { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "24-bit RGB background" + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[00;48;2;0;0;0m000|000|000 \u001b[00m\u001b[00;48;2;0;0;30m000|000|030 \u001b[00m\u001b[00;48;2;0;0;60m000|000|060 \u001b[00m\u001b[00;48;2;0;0;90m000|000|090 \u001b[00m\u001b[00;48;2;0;0;120m000|000|120 \u001b[00m\u001b[00;48;2;0;0;150m000|000|150 \u001b[00m\u001b[00;48;2;0;0;180m000|000|180 \u001b[00m\u001b[00;48;2;0;0;210m000|000|210 \u001b[00m\u001b[00;48;2;0;0;240m000|000|240 \u001b[00m\n", + "\u001b[00;48;2;0;30;0m000|030|000 \u001b[00m\u001b[00;48;2;0;30;30m000|030|030 \u001b[00m\u001b[00;48;2;0;30;60m000|030|060 \u001b[00m\u001b[00;48;2;0;30;90m000|030|090 \u001b[00m\u001b[00;48;2;0;30;120m000|030|120 \u001b[00m\u001b[00;48;2;0;30;150m000|030|150 \u001b[00m\u001b[00;48;2;0;30;180m000|030|180 \u001b[00m\u001b[00;48;2;0;30;210m000|030|210 \u001b[00m\u001b[00;48;2;0;30;240m000|030|240 \u001b[00m\n", + "\u001b[00;48;2;0;60;0m000|060|000 \u001b[00m\u001b[00;48;2;0;60;30m000|060|030 \u001b[00m\u001b[00;48;2;0;60;60m000|060|060 \u001b[00m\u001b[00;48;2;0;60;90m000|060|090 \u001b[00m\u001b[00;48;2;0;60;120m000|060|120 \u001b[00m\u001b[00;48;2;0;60;150m000|060|150 \u001b[00m\u001b[00;48;2;0;60;180m000|060|180 \u001b[00m\u001b[00;48;2;0;60;210m000|060|210 \u001b[00m\u001b[00;48;2;0;60;240m000|060|240 \u001b[00m\n", + "\u001b[00;48;2;0;90;0m000|090|000 \u001b[00m\u001b[00;48;2;0;90;30m000|090|030 \u001b[00m\u001b[00;48;2;0;90;60m000|090|060 \u001b[00m\u001b[00;48;2;0;90;90m000|090|090 \u001b[00m\u001b[00;48;2;0;90;120m000|090|120 \u001b[00m\u001b[00;48;2;0;90;150m000|090|150 \u001b[00m\u001b[00;48;2;0;90;180m000|090|180 \u001b[00m\u001b[00;48;2;0;90;210m000|090|210 \u001b[00m\u001b[00;48;2;0;90;240m000|090|240 \u001b[00m\n", + "\u001b[00;48;2;0;120;0m000|120|000 \u001b[00m\u001b[00;48;2;0;120;30m000|120|030 \u001b[00m\u001b[00;48;2;0;120;60m000|120|060 \u001b[00m\u001b[00;48;2;0;120;90m000|120|090 \u001b[00m\u001b[00;48;2;0;120;120m000|120|120 \u001b[00m\u001b[00;48;2;0;120;150m000|120|150 \u001b[00m\u001b[00;48;2;0;120;180m000|120|180 \u001b[00m\u001b[00;48;2;0;120;210m000|120|210 \u001b[00m\u001b[00;48;2;0;120;240m000|120|240 \u001b[00m\n", + "\u001b[00;48;2;0;150;0m000|150|000 \u001b[00m\u001b[00;48;2;0;150;30m000|150|030 \u001b[00m\u001b[00;48;2;0;150;60m000|150|060 \u001b[00m\u001b[00;48;2;0;150;90m000|150|090 \u001b[00m\u001b[00;48;2;0;150;120m000|150|120 \u001b[00m\u001b[00;48;2;0;150;150m000|150|150 \u001b[00m\u001b[00;48;2;0;150;180m000|150|180 \u001b[00m\u001b[00;48;2;0;150;210m000|150|210 \u001b[00m\u001b[00;48;2;0;150;240m000|150|240 \u001b[00m\n", + "\u001b[00;48;2;0;180;0m000|180|000 \u001b[00m\u001b[00;48;2;0;180;30m000|180|030 \u001b[00m\u001b[00;48;2;0;180;60m000|180|060 \u001b[00m\u001b[00;48;2;0;180;90m000|180|090 \u001b[00m\u001b[00;48;2;0;180;120m000|180|120 \u001b[00m\u001b[00;48;2;0;180;150m000|180|150 \u001b[00m\u001b[00;48;2;0;180;180m000|180|180 \u001b[00m\u001b[00;48;2;0;180;210m000|180|210 \u001b[00m\u001b[00;48;2;0;180;240m000|180|240 \u001b[00m\n", + "\u001b[00;48;2;0;210;0m000|210|000 \u001b[00m\u001b[00;48;2;0;210;30m000|210|030 \u001b[00m\u001b[00;48;2;0;210;60m000|210|060 \u001b[00m\u001b[00;48;2;0;210;90m000|210|090 \u001b[00m\u001b[00;48;2;0;210;120m000|210|120 \u001b[00m\u001b[00;48;2;0;210;150m000|210|150 \u001b[00m\u001b[00;48;2;0;210;180m000|210|180 \u001b[00m\u001b[00;48;2;0;210;210m000|210|210 \u001b[00m\u001b[00;48;2;0;210;240m000|210|240 \u001b[00m\n", + "\u001b[00;48;2;0;240;0m000|240|000 \u001b[00m\u001b[00;48;2;0;240;30m000|240|030 \u001b[00m\u001b[00;48;2;0;240;60m000|240|060 \u001b[00m\u001b[00;48;2;0;240;90m000|240|090 \u001b[00m\u001b[00;48;2;0;240;120m000|240|120 \u001b[00m\u001b[00;48;2;0;240;150m000|240|150 \u001b[00m\u001b[00;48;2;0;240;180m000|240|180 \u001b[00m\u001b[00;48;2;0;240;210m000|240|210 \u001b[00m\u001b[00;48;2;0;240;240m000|240|240 \u001b[00m\n", + "\n", + "\u001b[00;48;2;30;0;0m030|000|000 \u001b[00m\u001b[00;48;2;30;0;30m030|000|030 \u001b[00m\u001b[00;48;2;30;0;60m030|000|060 \u001b[00m\u001b[00;48;2;30;0;90m030|000|090 \u001b[00m\u001b[00;48;2;30;0;120m030|000|120 \u001b[00m\u001b[00;48;2;30;0;150m030|000|150 \u001b[00m\u001b[00;48;2;30;0;180m030|000|180 \u001b[00m\u001b[00;48;2;30;0;210m030|000|210 \u001b[00m\u001b[00;48;2;30;0;240m030|000|240 \u001b[00m\n", + "\u001b[00;48;2;30;30;0m030|030|000 \u001b[00m\u001b[00;48;2;30;30;30m030|030|030 \u001b[00m\u001b[00;48;2;30;30;60m030|030|060 \u001b[00m\u001b[00;48;2;30;30;90m030|030|090 \u001b[00m\u001b[00;48;2;30;30;120m030|030|120 \u001b[00m\u001b[00;48;2;30;30;150m030|030|150 \u001b[00m\u001b[00;48;2;30;30;180m030|030|180 \u001b[00m\u001b[00;48;2;30;30;210m030|030|210 \u001b[00m\u001b[00;48;2;30;30;240m030|030|240 \u001b[00m\n", + "\u001b[00;48;2;30;60;0m030|060|000 \u001b[00m\u001b[00;48;2;30;60;30m030|060|030 \u001b[00m\u001b[00;48;2;30;60;60m030|060|060 \u001b[00m\u001b[00;48;2;30;60;90m030|060|090 \u001b[00m\u001b[00;48;2;30;60;120m030|060|120 \u001b[00m\u001b[00;48;2;30;60;150m030|060|150 \u001b[00m\u001b[00;48;2;30;60;180m030|060|180 \u001b[00m\u001b[00;48;2;30;60;210m030|060|210 \u001b[00m\u001b[00;48;2;30;60;240m030|060|240 \u001b[00m\n", + "\u001b[00;48;2;30;90;0m030|090|000 \u001b[00m\u001b[00;48;2;30;90;30m030|090|030 \u001b[00m\u001b[00;48;2;30;90;60m030|090|060 \u001b[00m\u001b[00;48;2;30;90;90m030|090|090 \u001b[00m\u001b[00;48;2;30;90;120m030|090|120 \u001b[00m\u001b[00;48;2;30;90;150m030|090|150 \u001b[00m\u001b[00;48;2;30;90;180m030|090|180 \u001b[00m\u001b[00;48;2;30;90;210m030|090|210 \u001b[00m\u001b[00;48;2;30;90;240m030|090|240 \u001b[00m\n", + "\u001b[00;48;2;30;120;0m030|120|000 \u001b[00m\u001b[00;48;2;30;120;30m030|120|030 \u001b[00m\u001b[00;48;2;30;120;60m030|120|060 \u001b[00m\u001b[00;48;2;30;120;90m030|120|090 \u001b[00m\u001b[00;48;2;30;120;120m030|120|120 \u001b[00m\u001b[00;48;2;30;120;150m030|120|150 \u001b[00m\u001b[00;48;2;30;120;180m030|120|180 \u001b[00m\u001b[00;48;2;30;120;210m030|120|210 \u001b[00m\u001b[00;48;2;30;120;240m030|120|240 \u001b[00m\n", + "\u001b[00;48;2;30;150;0m030|150|000 \u001b[00m\u001b[00;48;2;30;150;30m030|150|030 \u001b[00m\u001b[00;48;2;30;150;60m030|150|060 \u001b[00m\u001b[00;48;2;30;150;90m030|150|090 \u001b[00m\u001b[00;48;2;30;150;120m030|150|120 \u001b[00m\u001b[00;48;2;30;150;150m030|150|150 \u001b[00m\u001b[00;48;2;30;150;180m030|150|180 \u001b[00m\u001b[00;48;2;30;150;210m030|150|210 \u001b[00m\u001b[00;48;2;30;150;240m030|150|240 \u001b[00m\n", + "\u001b[00;48;2;30;180;0m030|180|000 \u001b[00m\u001b[00;48;2;30;180;30m030|180|030 \u001b[00m\u001b[00;48;2;30;180;60m030|180|060 \u001b[00m\u001b[00;48;2;30;180;90m030|180|090 \u001b[00m\u001b[00;48;2;30;180;120m030|180|120 \u001b[00m\u001b[00;48;2;30;180;150m030|180|150 \u001b[00m\u001b[00;48;2;30;180;180m030|180|180 \u001b[00m\u001b[00;48;2;30;180;210m030|180|210 \u001b[00m\u001b[00;48;2;30;180;240m030|180|240 \u001b[00m\n", + "\u001b[00;48;2;30;210;0m030|210|000 \u001b[00m\u001b[00;48;2;30;210;30m030|210|030 \u001b[00m\u001b[00;48;2;30;210;60m030|210|060 \u001b[00m\u001b[00;48;2;30;210;90m030|210|090 \u001b[00m\u001b[00;48;2;30;210;120m030|210|120 \u001b[00m\u001b[00;48;2;30;210;150m030|210|150 \u001b[00m\u001b[00;48;2;30;210;180m030|210|180 \u001b[00m\u001b[00;48;2;30;210;210m030|210|210 \u001b[00m\u001b[00;48;2;30;210;240m030|210|240 \u001b[00m\n", + "\u001b[00;48;2;30;240;0m030|240|000 \u001b[00m\u001b[00;48;2;30;240;30m030|240|030 \u001b[00m\u001b[00;48;2;30;240;60m030|240|060 \u001b[00m\u001b[00;48;2;30;240;90m030|240|090 \u001b[00m\u001b[00;48;2;30;240;120m030|240|120 \u001b[00m\u001b[00;48;2;30;240;150m030|240|150 \u001b[00m\u001b[00;48;2;30;240;180m030|240|180 \u001b[00m\u001b[00;48;2;30;240;210m030|240|210 \u001b[00m\u001b[00;48;2;30;240;240m030|240|240 \u001b[00m\n", + "\n", + "\u001b[00;48;2;60;0;0m060|000|000 \u001b[00m\u001b[00;48;2;60;0;30m060|000|030 \u001b[00m\u001b[00;48;2;60;0;60m060|000|060 \u001b[00m\u001b[00;48;2;60;0;90m060|000|090 \u001b[00m\u001b[00;48;2;60;0;120m060|000|120 \u001b[00m\u001b[00;48;2;60;0;150m060|000|150 \u001b[00m\u001b[00;48;2;60;0;180m060|000|180 \u001b[00m\u001b[00;48;2;60;0;210m060|000|210 \u001b[00m\u001b[00;48;2;60;0;240m060|000|240 \u001b[00m\n", + "\u001b[00;48;2;60;30;0m060|030|000 \u001b[00m\u001b[00;48;2;60;30;30m060|030|030 \u001b[00m\u001b[00;48;2;60;30;60m060|030|060 \u001b[00m\u001b[00;48;2;60;30;90m060|030|090 \u001b[00m\u001b[00;48;2;60;30;120m060|030|120 \u001b[00m\u001b[00;48;2;60;30;150m060|030|150 \u001b[00m\u001b[00;48;2;60;30;180m060|030|180 \u001b[00m\u001b[00;48;2;60;30;210m060|030|210 \u001b[00m\u001b[00;48;2;60;30;240m060|030|240 \u001b[00m\n", + "\u001b[00;48;2;60;60;0m060|060|000 \u001b[00m\u001b[00;48;2;60;60;30m060|060|030 \u001b[00m\u001b[00;48;2;60;60;60m060|060|060 \u001b[00m\u001b[00;48;2;60;60;90m060|060|090 \u001b[00m\u001b[00;48;2;60;60;120m060|060|120 \u001b[00m\u001b[00;48;2;60;60;150m060|060|150 \u001b[00m\u001b[00;48;2;60;60;180m060|060|180 \u001b[00m\u001b[00;48;2;60;60;210m060|060|210 \u001b[00m\u001b[00;48;2;60;60;240m060|060|240 \u001b[00m\n", + "\u001b[00;48;2;60;90;0m060|090|000 \u001b[00m\u001b[00;48;2;60;90;30m060|090|030 \u001b[00m\u001b[00;48;2;60;90;60m060|090|060 \u001b[00m\u001b[00;48;2;60;90;90m060|090|090 \u001b[00m\u001b[00;48;2;60;90;120m060|090|120 \u001b[00m\u001b[00;48;2;60;90;150m060|090|150 \u001b[00m\u001b[00;48;2;60;90;180m060|090|180 \u001b[00m\u001b[00;48;2;60;90;210m060|090|210 \u001b[00m\u001b[00;48;2;60;90;240m060|090|240 \u001b[00m\n", + "\u001b[00;48;2;60;120;0m060|120|000 \u001b[00m\u001b[00;48;2;60;120;30m060|120|030 \u001b[00m\u001b[00;48;2;60;120;60m060|120|060 \u001b[00m\u001b[00;48;2;60;120;90m060|120|090 \u001b[00m\u001b[00;48;2;60;120;120m060|120|120 \u001b[00m\u001b[00;48;2;60;120;150m060|120|150 \u001b[00m\u001b[00;48;2;60;120;180m060|120|180 \u001b[00m\u001b[00;48;2;60;120;210m060|120|210 \u001b[00m\u001b[00;48;2;60;120;240m060|120|240 \u001b[00m\n", + "\u001b[00;48;2;60;150;0m060|150|000 \u001b[00m\u001b[00;48;2;60;150;30m060|150|030 \u001b[00m\u001b[00;48;2;60;150;60m060|150|060 \u001b[00m\u001b[00;48;2;60;150;90m060|150|090 \u001b[00m\u001b[00;48;2;60;150;120m060|150|120 \u001b[00m\u001b[00;48;2;60;150;150m060|150|150 \u001b[00m\u001b[00;48;2;60;150;180m060|150|180 \u001b[00m\u001b[00;48;2;60;150;210m060|150|210 \u001b[00m\u001b[00;48;2;60;150;240m060|150|240 \u001b[00m\n", + "\u001b[00;48;2;60;180;0m060|180|000 \u001b[00m\u001b[00;48;2;60;180;30m060|180|030 \u001b[00m\u001b[00;48;2;60;180;60m060|180|060 \u001b[00m\u001b[00;48;2;60;180;90m060|180|090 \u001b[00m\u001b[00;48;2;60;180;120m060|180|120 \u001b[00m\u001b[00;48;2;60;180;150m060|180|150 \u001b[00m\u001b[00;48;2;60;180;180m060|180|180 \u001b[00m\u001b[00;48;2;60;180;210m060|180|210 \u001b[00m\u001b[00;48;2;60;180;240m060|180|240 \u001b[00m\n", + "\u001b[00;48;2;60;210;0m060|210|000 \u001b[00m\u001b[00;48;2;60;210;30m060|210|030 \u001b[00m\u001b[00;48;2;60;210;60m060|210|060 \u001b[00m\u001b[00;48;2;60;210;90m060|210|090 \u001b[00m\u001b[00;48;2;60;210;120m060|210|120 \u001b[00m\u001b[00;48;2;60;210;150m060|210|150 \u001b[00m\u001b[00;48;2;60;210;180m060|210|180 \u001b[00m\u001b[00;48;2;60;210;210m060|210|210 \u001b[00m\u001b[00;48;2;60;210;240m060|210|240 \u001b[00m\n", + "\u001b[00;48;2;60;240;0m060|240|000 \u001b[00m\u001b[00;48;2;60;240;30m060|240|030 \u001b[00m\u001b[00;48;2;60;240;60m060|240|060 \u001b[00m\u001b[00;48;2;60;240;90m060|240|090 \u001b[00m\u001b[00;48;2;60;240;120m060|240|120 \u001b[00m\u001b[00;48;2;60;240;150m060|240|150 \u001b[00m\u001b[00;48;2;60;240;180m060|240|180 \u001b[00m\u001b[00;48;2;60;240;210m060|240|210 \u001b[00m\u001b[00;48;2;60;240;240m060|240|240 \u001b[00m\n", + "\n", + "\u001b[00;48;2;90;0;0m090|000|000 \u001b[00m\u001b[00;48;2;90;0;30m090|000|030 \u001b[00m\u001b[00;48;2;90;0;60m090|000|060 \u001b[00m\u001b[00;48;2;90;0;90m090|000|090 \u001b[00m\u001b[00;48;2;90;0;120m090|000|120 \u001b[00m\u001b[00;48;2;90;0;150m090|000|150 \u001b[00m\u001b[00;48;2;90;0;180m090|000|180 \u001b[00m\u001b[00;48;2;90;0;210m090|000|210 \u001b[00m\u001b[00;48;2;90;0;240m090|000|240 \u001b[00m\n", + "\u001b[00;48;2;90;30;0m090|030|000 \u001b[00m\u001b[00;48;2;90;30;30m090|030|030 \u001b[00m\u001b[00;48;2;90;30;60m090|030|060 \u001b[00m\u001b[00;48;2;90;30;90m090|030|090 \u001b[00m\u001b[00;48;2;90;30;120m090|030|120 \u001b[00m\u001b[00;48;2;90;30;150m090|030|150 \u001b[00m\u001b[00;48;2;90;30;180m090|030|180 \u001b[00m\u001b[00;48;2;90;30;210m090|030|210 \u001b[00m\u001b[00;48;2;90;30;240m090|030|240 \u001b[00m\n", + "\u001b[00;48;2;90;60;0m090|060|000 \u001b[00m\u001b[00;48;2;90;60;30m090|060|030 \u001b[00m\u001b[00;48;2;90;60;60m090|060|060 \u001b[00m\u001b[00;48;2;90;60;90m090|060|090 \u001b[00m\u001b[00;48;2;90;60;120m090|060|120 \u001b[00m\u001b[00;48;2;90;60;150m090|060|150 \u001b[00m\u001b[00;48;2;90;60;180m090|060|180 \u001b[00m\u001b[00;48;2;90;60;210m090|060|210 \u001b[00m\u001b[00;48;2;90;60;240m090|060|240 \u001b[00m\n", + "\u001b[00;48;2;90;90;0m090|090|000 \u001b[00m\u001b[00;48;2;90;90;30m090|090|030 \u001b[00m\u001b[00;48;2;90;90;60m090|090|060 \u001b[00m\u001b[00;48;2;90;90;90m090|090|090 \u001b[00m\u001b[00;48;2;90;90;120m090|090|120 \u001b[00m\u001b[00;48;2;90;90;150m090|090|150 \u001b[00m\u001b[00;48;2;90;90;180m090|090|180 \u001b[00m\u001b[00;48;2;90;90;210m090|090|210 \u001b[00m\u001b[00;48;2;90;90;240m090|090|240 \u001b[00m\n", + "\u001b[00;48;2;90;120;0m090|120|000 \u001b[00m\u001b[00;48;2;90;120;30m090|120|030 \u001b[00m\u001b[00;48;2;90;120;60m090|120|060 \u001b[00m\u001b[00;48;2;90;120;90m090|120|090 \u001b[00m\u001b[00;48;2;90;120;120m090|120|120 \u001b[00m\u001b[00;48;2;90;120;150m090|120|150 \u001b[00m\u001b[00;48;2;90;120;180m090|120|180 \u001b[00m\u001b[00;48;2;90;120;210m090|120|210 \u001b[00m\u001b[00;48;2;90;120;240m090|120|240 \u001b[00m\n", + "\u001b[00;48;2;90;150;0m090|150|000 \u001b[00m\u001b[00;48;2;90;150;30m090|150|030 \u001b[00m\u001b[00;48;2;90;150;60m090|150|060 \u001b[00m\u001b[00;48;2;90;150;90m090|150|090 \u001b[00m\u001b[00;48;2;90;150;120m090|150|120 \u001b[00m\u001b[00;48;2;90;150;150m090|150|150 \u001b[00m\u001b[00;48;2;90;150;180m090|150|180 \u001b[00m\u001b[00;48;2;90;150;210m090|150|210 \u001b[00m\u001b[00;48;2;90;150;240m090|150|240 \u001b[00m\n", + "\u001b[00;48;2;90;180;0m090|180|000 \u001b[00m\u001b[00;48;2;90;180;30m090|180|030 \u001b[00m\u001b[00;48;2;90;180;60m090|180|060 \u001b[00m\u001b[00;48;2;90;180;90m090|180|090 \u001b[00m\u001b[00;48;2;90;180;120m090|180|120 \u001b[00m\u001b[00;48;2;90;180;150m090|180|150 \u001b[00m\u001b[00;48;2;90;180;180m090|180|180 \u001b[00m\u001b[00;48;2;90;180;210m090|180|210 \u001b[00m\u001b[00;48;2;90;180;240m090|180|240 \u001b[00m\n", + "\u001b[00;48;2;90;210;0m090|210|000 \u001b[00m\u001b[00;48;2;90;210;30m090|210|030 \u001b[00m\u001b[00;48;2;90;210;60m090|210|060 \u001b[00m\u001b[00;48;2;90;210;90m090|210|090 \u001b[00m\u001b[00;48;2;90;210;120m090|210|120 \u001b[00m\u001b[00;48;2;90;210;150m090|210|150 \u001b[00m\u001b[00;48;2;90;210;180m090|210|180 \u001b[00m\u001b[00;48;2;90;210;210m090|210|210 \u001b[00m\u001b[00;48;2;90;210;240m090|210|240 \u001b[00m\n", + "\u001b[00;48;2;90;240;0m090|240|000 \u001b[00m\u001b[00;48;2;90;240;30m090|240|030 \u001b[00m\u001b[00;48;2;90;240;60m090|240|060 \u001b[00m\u001b[00;48;2;90;240;90m090|240|090 \u001b[00m\u001b[00;48;2;90;240;120m090|240|120 \u001b[00m\u001b[00;48;2;90;240;150m090|240|150 \u001b[00m\u001b[00;48;2;90;240;180m090|240|180 \u001b[00m\u001b[00;48;2;90;240;210m090|240|210 \u001b[00m\u001b[00;48;2;90;240;240m090|240|240 \u001b[00m\n", + "\n", + "\u001b[00;48;2;120;0;0m120|000|000 \u001b[00m\u001b[00;48;2;120;0;30m120|000|030 \u001b[00m\u001b[00;48;2;120;0;60m120|000|060 \u001b[00m\u001b[00;48;2;120;0;90m120|000|090 \u001b[00m\u001b[00;48;2;120;0;120m120|000|120 \u001b[00m\u001b[00;48;2;120;0;150m120|000|150 \u001b[00m\u001b[00;48;2;120;0;180m120|000|180 \u001b[00m\u001b[00;48;2;120;0;210m120|000|210 \u001b[00m\u001b[00;48;2;120;0;240m120|000|240 \u001b[00m\n", + "\u001b[00;48;2;120;30;0m120|030|000 \u001b[00m\u001b[00;48;2;120;30;30m120|030|030 \u001b[00m\u001b[00;48;2;120;30;60m120|030|060 \u001b[00m\u001b[00;48;2;120;30;90m120|030|090 \u001b[00m\u001b[00;48;2;120;30;120m120|030|120 \u001b[00m\u001b[00;48;2;120;30;150m120|030|150 \u001b[00m\u001b[00;48;2;120;30;180m120|030|180 \u001b[00m\u001b[00;48;2;120;30;210m120|030|210 \u001b[00m\u001b[00;48;2;120;30;240m120|030|240 \u001b[00m\n", + "\u001b[00;48;2;120;60;0m120|060|000 \u001b[00m\u001b[00;48;2;120;60;30m120|060|030 \u001b[00m\u001b[00;48;2;120;60;60m120|060|060 \u001b[00m\u001b[00;48;2;120;60;90m120|060|090 \u001b[00m\u001b[00;48;2;120;60;120m120|060|120 \u001b[00m\u001b[00;48;2;120;60;150m120|060|150 \u001b[00m\u001b[00;48;2;120;60;180m120|060|180 \u001b[00m\u001b[00;48;2;120;60;210m120|060|210 \u001b[00m\u001b[00;48;2;120;60;240m120|060|240 \u001b[00m\n", + "\u001b[00;48;2;120;90;0m120|090|000 \u001b[00m\u001b[00;48;2;120;90;30m120|090|030 \u001b[00m\u001b[00;48;2;120;90;60m120|090|060 \u001b[00m\u001b[00;48;2;120;90;90m120|090|090 \u001b[00m\u001b[00;48;2;120;90;120m120|090|120 \u001b[00m\u001b[00;48;2;120;90;150m120|090|150 \u001b[00m\u001b[00;48;2;120;90;180m120|090|180 \u001b[00m\u001b[00;48;2;120;90;210m120|090|210 \u001b[00m\u001b[00;48;2;120;90;240m120|090|240 \u001b[00m\n", + "\u001b[00;48;2;120;120;0m120|120|000 \u001b[00m\u001b[00;48;2;120;120;30m120|120|030 \u001b[00m\u001b[00;48;2;120;120;60m120|120|060 \u001b[00m\u001b[00;48;2;120;120;90m120|120|090 \u001b[00m\u001b[00;48;2;120;120;120m120|120|120 \u001b[00m\u001b[00;48;2;120;120;150m120|120|150 \u001b[00m\u001b[00;48;2;120;120;180m120|120|180 \u001b[00m\u001b[00;48;2;120;120;210m120|120|210 \u001b[00m\u001b[00;48;2;120;120;240m120|120|240 \u001b[00m\n", + "\u001b[00;48;2;120;150;0m120|150|000 \u001b[00m\u001b[00;48;2;120;150;30m120|150|030 \u001b[00m\u001b[00;48;2;120;150;60m120|150|060 \u001b[00m\u001b[00;48;2;120;150;90m120|150|090 \u001b[00m\u001b[00;48;2;120;150;120m120|150|120 \u001b[00m\u001b[00;48;2;120;150;150m120|150|150 \u001b[00m\u001b[00;48;2;120;150;180m120|150|180 \u001b[00m\u001b[00;48;2;120;150;210m120|150|210 \u001b[00m\u001b[00;48;2;120;150;240m120|150|240 \u001b[00m\n", + "\u001b[00;48;2;120;180;0m120|180|000 \u001b[00m\u001b[00;48;2;120;180;30m120|180|030 \u001b[00m\u001b[00;48;2;120;180;60m120|180|060 \u001b[00m\u001b[00;48;2;120;180;90m120|180|090 \u001b[00m\u001b[00;48;2;120;180;120m120|180|120 \u001b[00m\u001b[00;48;2;120;180;150m120|180|150 \u001b[00m\u001b[00;48;2;120;180;180m120|180|180 \u001b[00m\u001b[00;48;2;120;180;210m120|180|210 \u001b[00m\u001b[00;48;2;120;180;240m120|180|240 \u001b[00m\n", + "\u001b[00;48;2;120;210;0m120|210|000 \u001b[00m\u001b[00;48;2;120;210;30m120|210|030 \u001b[00m\u001b[00;48;2;120;210;60m120|210|060 \u001b[00m\u001b[00;48;2;120;210;90m120|210|090 \u001b[00m\u001b[00;48;2;120;210;120m120|210|120 \u001b[00m\u001b[00;48;2;120;210;150m120|210|150 \u001b[00m\u001b[00;48;2;120;210;180m120|210|180 \u001b[00m\u001b[00;48;2;120;210;210m120|210|210 \u001b[00m\u001b[00;48;2;120;210;240m120|210|240 \u001b[00m\n", + "\u001b[00;48;2;120;240;0m120|240|000 \u001b[00m\u001b[00;48;2;120;240;30m120|240|030 \u001b[00m\u001b[00;48;2;120;240;60m120|240|060 \u001b[00m\u001b[00;48;2;120;240;90m120|240|090 \u001b[00m\u001b[00;48;2;120;240;120m120|240|120 \u001b[00m\u001b[00;48;2;120;240;150m120|240|150 \u001b[00m\u001b[00;48;2;120;240;180m120|240|180 \u001b[00m\u001b[00;48;2;120;240;210m120|240|210 \u001b[00m\u001b[00;48;2;120;240;240m120|240|240 \u001b[00m\n", + "\n", + "\u001b[00;48;2;150;0;0m150|000|000 \u001b[00m\u001b[00;48;2;150;0;30m150|000|030 \u001b[00m\u001b[00;48;2;150;0;60m150|000|060 \u001b[00m\u001b[00;48;2;150;0;90m150|000|090 \u001b[00m\u001b[00;48;2;150;0;120m150|000|120 \u001b[00m\u001b[00;48;2;150;0;150m150|000|150 \u001b[00m\u001b[00;48;2;150;0;180m150|000|180 \u001b[00m\u001b[00;48;2;150;0;210m150|000|210 \u001b[00m\u001b[00;48;2;150;0;240m150|000|240 \u001b[00m\n", + "\u001b[00;48;2;150;30;0m150|030|000 \u001b[00m\u001b[00;48;2;150;30;30m150|030|030 \u001b[00m\u001b[00;48;2;150;30;60m150|030|060 \u001b[00m\u001b[00;48;2;150;30;90m150|030|090 \u001b[00m\u001b[00;48;2;150;30;120m150|030|120 \u001b[00m\u001b[00;48;2;150;30;150m150|030|150 \u001b[00m\u001b[00;48;2;150;30;180m150|030|180 \u001b[00m\u001b[00;48;2;150;30;210m150|030|210 \u001b[00m\u001b[00;48;2;150;30;240m150|030|240 \u001b[00m\n", + "\u001b[00;48;2;150;60;0m150|060|000 \u001b[00m\u001b[00;48;2;150;60;30m150|060|030 \u001b[00m\u001b[00;48;2;150;60;60m150|060|060 \u001b[00m\u001b[00;48;2;150;60;90m150|060|090 \u001b[00m\u001b[00;48;2;150;60;120m150|060|120 \u001b[00m\u001b[00;48;2;150;60;150m150|060|150 \u001b[00m\u001b[00;48;2;150;60;180m150|060|180 \u001b[00m\u001b[00;48;2;150;60;210m150|060|210 \u001b[00m\u001b[00;48;2;150;60;240m150|060|240 \u001b[00m\n", + "\u001b[00;48;2;150;90;0m150|090|000 \u001b[00m\u001b[00;48;2;150;90;30m150|090|030 \u001b[00m\u001b[00;48;2;150;90;60m150|090|060 \u001b[00m\u001b[00;48;2;150;90;90m150|090|090 \u001b[00m\u001b[00;48;2;150;90;120m150|090|120 \u001b[00m\u001b[00;48;2;150;90;150m150|090|150 \u001b[00m\u001b[00;48;2;150;90;180m150|090|180 \u001b[00m\u001b[00;48;2;150;90;210m150|090|210 \u001b[00m\u001b[00;48;2;150;90;240m150|090|240 \u001b[00m\n", + "\u001b[00;48;2;150;120;0m150|120|000 \u001b[00m\u001b[00;48;2;150;120;30m150|120|030 \u001b[00m\u001b[00;48;2;150;120;60m150|120|060 \u001b[00m\u001b[00;48;2;150;120;90m150|120|090 \u001b[00m\u001b[00;48;2;150;120;120m150|120|120 \u001b[00m\u001b[00;48;2;150;120;150m150|120|150 \u001b[00m\u001b[00;48;2;150;120;180m150|120|180 \u001b[00m\u001b[00;48;2;150;120;210m150|120|210 \u001b[00m\u001b[00;48;2;150;120;240m150|120|240 \u001b[00m\n", + "\u001b[00;48;2;150;150;0m150|150|000 \u001b[00m\u001b[00;48;2;150;150;30m150|150|030 \u001b[00m\u001b[00;48;2;150;150;60m150|150|060 \u001b[00m\u001b[00;48;2;150;150;90m150|150|090 \u001b[00m\u001b[00;48;2;150;150;120m150|150|120 \u001b[00m\u001b[00;48;2;150;150;150m150|150|150 \u001b[00m\u001b[00;48;2;150;150;180m150|150|180 \u001b[00m\u001b[00;48;2;150;150;210m150|150|210 \u001b[00m\u001b[00;48;2;150;150;240m150|150|240 \u001b[00m\n", + "\u001b[00;48;2;150;180;0m150|180|000 \u001b[00m\u001b[00;48;2;150;180;30m150|180|030 \u001b[00m\u001b[00;48;2;150;180;60m150|180|060 \u001b[00m\u001b[00;48;2;150;180;90m150|180|090 \u001b[00m\u001b[00;48;2;150;180;120m150|180|120 \u001b[00m\u001b[00;48;2;150;180;150m150|180|150 \u001b[00m\u001b[00;48;2;150;180;180m150|180|180 \u001b[00m\u001b[00;48;2;150;180;210m150|180|210 \u001b[00m\u001b[00;48;2;150;180;240m150|180|240 \u001b[00m\n", + "\u001b[00;48;2;150;210;0m150|210|000 \u001b[00m\u001b[00;48;2;150;210;30m150|210|030 \u001b[00m\u001b[00;48;2;150;210;60m150|210|060 \u001b[00m\u001b[00;48;2;150;210;90m150|210|090 \u001b[00m\u001b[00;48;2;150;210;120m150|210|120 \u001b[00m\u001b[00;48;2;150;210;150m150|210|150 \u001b[00m\u001b[00;48;2;150;210;180m150|210|180 \u001b[00m\u001b[00;48;2;150;210;210m150|210|210 \u001b[00m\u001b[00;48;2;150;210;240m150|210|240 \u001b[00m\n", + "\u001b[00;48;2;150;240;0m150|240|000 \u001b[00m\u001b[00;48;2;150;240;30m150|240|030 \u001b[00m\u001b[00;48;2;150;240;60m150|240|060 \u001b[00m\u001b[00;48;2;150;240;90m150|240|090 \u001b[00m\u001b[00;48;2;150;240;120m150|240|120 \u001b[00m\u001b[00;48;2;150;240;150m150|240|150 \u001b[00m\u001b[00;48;2;150;240;180m150|240|180 \u001b[00m\u001b[00;48;2;150;240;210m150|240|210 \u001b[00m\u001b[00;48;2;150;240;240m150|240|240 \u001b[00m\n", + "\n", + "\u001b[00;48;2;180;0;0m180|000|000 \u001b[00m\u001b[00;48;2;180;0;30m180|000|030 \u001b[00m\u001b[00;48;2;180;0;60m180|000|060 \u001b[00m\u001b[00;48;2;180;0;90m180|000|090 \u001b[00m\u001b[00;48;2;180;0;120m180|000|120 \u001b[00m\u001b[00;48;2;180;0;150m180|000|150 \u001b[00m\u001b[00;48;2;180;0;180m180|000|180 \u001b[00m\u001b[00;48;2;180;0;210m180|000|210 \u001b[00m\u001b[00;48;2;180;0;240m180|000|240 \u001b[00m\n", + "\u001b[00;48;2;180;30;0m180|030|000 \u001b[00m\u001b[00;48;2;180;30;30m180|030|030 \u001b[00m\u001b[00;48;2;180;30;60m180|030|060 \u001b[00m\u001b[00;48;2;180;30;90m180|030|090 \u001b[00m\u001b[00;48;2;180;30;120m180|030|120 \u001b[00m\u001b[00;48;2;180;30;150m180|030|150 \u001b[00m\u001b[00;48;2;180;30;180m180|030|180 \u001b[00m\u001b[00;48;2;180;30;210m180|030|210 \u001b[00m\u001b[00;48;2;180;30;240m180|030|240 \u001b[00m\n", + "\u001b[00;48;2;180;60;0m180|060|000 \u001b[00m\u001b[00;48;2;180;60;30m180|060|030 \u001b[00m\u001b[00;48;2;180;60;60m180|060|060 \u001b[00m\u001b[00;48;2;180;60;90m180|060|090 \u001b[00m\u001b[00;48;2;180;60;120m180|060|120 \u001b[00m\u001b[00;48;2;180;60;150m180|060|150 \u001b[00m\u001b[00;48;2;180;60;180m180|060|180 \u001b[00m\u001b[00;48;2;180;60;210m180|060|210 \u001b[00m\u001b[00;48;2;180;60;240m180|060|240 \u001b[00m\n", + "\u001b[00;48;2;180;90;0m180|090|000 \u001b[00m\u001b[00;48;2;180;90;30m180|090|030 \u001b[00m\u001b[00;48;2;180;90;60m180|090|060 \u001b[00m\u001b[00;48;2;180;90;90m180|090|090 \u001b[00m\u001b[00;48;2;180;90;120m180|090|120 \u001b[00m\u001b[00;48;2;180;90;150m180|090|150 \u001b[00m\u001b[00;48;2;180;90;180m180|090|180 \u001b[00m\u001b[00;48;2;180;90;210m180|090|210 \u001b[00m\u001b[00;48;2;180;90;240m180|090|240 \u001b[00m\n", + "\u001b[00;48;2;180;120;0m180|120|000 \u001b[00m\u001b[00;48;2;180;120;30m180|120|030 \u001b[00m\u001b[00;48;2;180;120;60m180|120|060 \u001b[00m\u001b[00;48;2;180;120;90m180|120|090 \u001b[00m\u001b[00;48;2;180;120;120m180|120|120 \u001b[00m\u001b[00;48;2;180;120;150m180|120|150 \u001b[00m\u001b[00;48;2;180;120;180m180|120|180 \u001b[00m\u001b[00;48;2;180;120;210m180|120|210 \u001b[00m\u001b[00;48;2;180;120;240m180|120|240 \u001b[00m\n", + "\u001b[00;48;2;180;150;0m180|150|000 \u001b[00m\u001b[00;48;2;180;150;30m180|150|030 \u001b[00m\u001b[00;48;2;180;150;60m180|150|060 \u001b[00m\u001b[00;48;2;180;150;90m180|150|090 \u001b[00m\u001b[00;48;2;180;150;120m180|150|120 \u001b[00m\u001b[00;48;2;180;150;150m180|150|150 \u001b[00m\u001b[00;48;2;180;150;180m180|150|180 \u001b[00m\u001b[00;48;2;180;150;210m180|150|210 \u001b[00m\u001b[00;48;2;180;150;240m180|150|240 \u001b[00m\n", + "\u001b[00;48;2;180;180;0m180|180|000 \u001b[00m\u001b[00;48;2;180;180;30m180|180|030 \u001b[00m\u001b[00;48;2;180;180;60m180|180|060 \u001b[00m\u001b[00;48;2;180;180;90m180|180|090 \u001b[00m\u001b[00;48;2;180;180;120m180|180|120 \u001b[00m\u001b[00;48;2;180;180;150m180|180|150 \u001b[00m\u001b[00;48;2;180;180;180m180|180|180 \u001b[00m\u001b[00;48;2;180;180;210m180|180|210 \u001b[00m\u001b[00;48;2;180;180;240m180|180|240 \u001b[00m\n", + "\u001b[00;48;2;180;210;0m180|210|000 \u001b[00m\u001b[00;48;2;180;210;30m180|210|030 \u001b[00m\u001b[00;48;2;180;210;60m180|210|060 \u001b[00m\u001b[00;48;2;180;210;90m180|210|090 \u001b[00m\u001b[00;48;2;180;210;120m180|210|120 \u001b[00m\u001b[00;48;2;180;210;150m180|210|150 \u001b[00m\u001b[00;48;2;180;210;180m180|210|180 \u001b[00m\u001b[00;48;2;180;210;210m180|210|210 \u001b[00m\u001b[00;48;2;180;210;240m180|210|240 \u001b[00m\n", + "\u001b[00;48;2;180;240;0m180|240|000 \u001b[00m\u001b[00;48;2;180;240;30m180|240|030 \u001b[00m\u001b[00;48;2;180;240;60m180|240|060 \u001b[00m\u001b[00;48;2;180;240;90m180|240|090 \u001b[00m\u001b[00;48;2;180;240;120m180|240|120 \u001b[00m\u001b[00;48;2;180;240;150m180|240|150 \u001b[00m\u001b[00;48;2;180;240;180m180|240|180 \u001b[00m\u001b[00;48;2;180;240;210m180|240|210 \u001b[00m\u001b[00;48;2;180;240;240m180|240|240 \u001b[00m\n", + "\n", + "\u001b[00;48;2;210;0;0m210|000|000 \u001b[00m\u001b[00;48;2;210;0;30m210|000|030 \u001b[00m\u001b[00;48;2;210;0;60m210|000|060 \u001b[00m\u001b[00;48;2;210;0;90m210|000|090 \u001b[00m\u001b[00;48;2;210;0;120m210|000|120 \u001b[00m\u001b[00;48;2;210;0;150m210|000|150 \u001b[00m\u001b[00;48;2;210;0;180m210|000|180 \u001b[00m\u001b[00;48;2;210;0;210m210|000|210 \u001b[00m\u001b[00;48;2;210;0;240m210|000|240 \u001b[00m\n", + "\u001b[00;48;2;210;30;0m210|030|000 \u001b[00m\u001b[00;48;2;210;30;30m210|030|030 \u001b[00m\u001b[00;48;2;210;30;60m210|030|060 \u001b[00m\u001b[00;48;2;210;30;90m210|030|090 \u001b[00m\u001b[00;48;2;210;30;120m210|030|120 \u001b[00m\u001b[00;48;2;210;30;150m210|030|150 \u001b[00m\u001b[00;48;2;210;30;180m210|030|180 \u001b[00m\u001b[00;48;2;210;30;210m210|030|210 \u001b[00m\u001b[00;48;2;210;30;240m210|030|240 \u001b[00m\n", + "\u001b[00;48;2;210;60;0m210|060|000 \u001b[00m\u001b[00;48;2;210;60;30m210|060|030 \u001b[00m\u001b[00;48;2;210;60;60m210|060|060 \u001b[00m\u001b[00;48;2;210;60;90m210|060|090 \u001b[00m\u001b[00;48;2;210;60;120m210|060|120 \u001b[00m\u001b[00;48;2;210;60;150m210|060|150 \u001b[00m\u001b[00;48;2;210;60;180m210|060|180 \u001b[00m\u001b[00;48;2;210;60;210m210|060|210 \u001b[00m\u001b[00;48;2;210;60;240m210|060|240 \u001b[00m\n", + "\u001b[00;48;2;210;90;0m210|090|000 \u001b[00m\u001b[00;48;2;210;90;30m210|090|030 \u001b[00m\u001b[00;48;2;210;90;60m210|090|060 \u001b[00m\u001b[00;48;2;210;90;90m210|090|090 \u001b[00m\u001b[00;48;2;210;90;120m210|090|120 \u001b[00m\u001b[00;48;2;210;90;150m210|090|150 \u001b[00m\u001b[00;48;2;210;90;180m210|090|180 \u001b[00m\u001b[00;48;2;210;90;210m210|090|210 \u001b[00m\u001b[00;48;2;210;90;240m210|090|240 \u001b[00m\n", + "\u001b[00;48;2;210;120;0m210|120|000 \u001b[00m\u001b[00;48;2;210;120;30m210|120|030 \u001b[00m\u001b[00;48;2;210;120;60m210|120|060 \u001b[00m\u001b[00;48;2;210;120;90m210|120|090 \u001b[00m\u001b[00;48;2;210;120;120m210|120|120 \u001b[00m\u001b[00;48;2;210;120;150m210|120|150 \u001b[00m\u001b[00;48;2;210;120;180m210|120|180 \u001b[00m\u001b[00;48;2;210;120;210m210|120|210 \u001b[00m\u001b[00;48;2;210;120;240m210|120|240 \u001b[00m\n", + "\u001b[00;48;2;210;150;0m210|150|000 \u001b[00m\u001b[00;48;2;210;150;30m210|150|030 \u001b[00m\u001b[00;48;2;210;150;60m210|150|060 \u001b[00m\u001b[00;48;2;210;150;90m210|150|090 \u001b[00m\u001b[00;48;2;210;150;120m210|150|120 \u001b[00m\u001b[00;48;2;210;150;150m210|150|150 \u001b[00m\u001b[00;48;2;210;150;180m210|150|180 \u001b[00m\u001b[00;48;2;210;150;210m210|150|210 \u001b[00m\u001b[00;48;2;210;150;240m210|150|240 \u001b[00m\n", + "\u001b[00;48;2;210;180;0m210|180|000 \u001b[00m\u001b[00;48;2;210;180;30m210|180|030 \u001b[00m\u001b[00;48;2;210;180;60m210|180|060 \u001b[00m\u001b[00;48;2;210;180;90m210|180|090 \u001b[00m\u001b[00;48;2;210;180;120m210|180|120 \u001b[00m\u001b[00;48;2;210;180;150m210|180|150 \u001b[00m\u001b[00;48;2;210;180;180m210|180|180 \u001b[00m\u001b[00;48;2;210;180;210m210|180|210 \u001b[00m\u001b[00;48;2;210;180;240m210|180|240 \u001b[00m\n", + "\u001b[00;48;2;210;210;0m210|210|000 \u001b[00m\u001b[00;48;2;210;210;30m210|210|030 \u001b[00m\u001b[00;48;2;210;210;60m210|210|060 \u001b[00m\u001b[00;48;2;210;210;90m210|210|090 \u001b[00m\u001b[00;48;2;210;210;120m210|210|120 \u001b[00m\u001b[00;48;2;210;210;150m210|210|150 \u001b[00m\u001b[00;48;2;210;210;180m210|210|180 \u001b[00m\u001b[00;48;2;210;210;210m210|210|210 \u001b[00m\u001b[00;48;2;210;210;240m210|210|240 \u001b[00m\n", + "\u001b[00;48;2;210;240;0m210|240|000 \u001b[00m\u001b[00;48;2;210;240;30m210|240|030 \u001b[00m\u001b[00;48;2;210;240;60m210|240|060 \u001b[00m\u001b[00;48;2;210;240;90m210|240|090 \u001b[00m\u001b[00;48;2;210;240;120m210|240|120 \u001b[00m\u001b[00;48;2;210;240;150m210|240|150 \u001b[00m\u001b[00;48;2;210;240;180m210|240|180 \u001b[00m\u001b[00;48;2;210;240;210m210|240|210 \u001b[00m\u001b[00;48;2;210;240;240m210|240|240 \u001b[00m\n", + "\n", + "\u001b[00;48;2;240;0;0m240|000|000 \u001b[00m\u001b[00;48;2;240;0;30m240|000|030 \u001b[00m\u001b[00;48;2;240;0;60m240|000|060 \u001b[00m\u001b[00;48;2;240;0;90m240|000|090 \u001b[00m\u001b[00;48;2;240;0;120m240|000|120 \u001b[00m\u001b[00;48;2;240;0;150m240|000|150 \u001b[00m\u001b[00;48;2;240;0;180m240|000|180 \u001b[00m\u001b[00;48;2;240;0;210m240|000|210 \u001b[00m\u001b[00;48;2;240;0;240m240|000|240 \u001b[00m\n", + "\u001b[00;48;2;240;30;0m240|030|000 \u001b[00m\u001b[00;48;2;240;30;30m240|030|030 \u001b[00m\u001b[00;48;2;240;30;60m240|030|060 \u001b[00m\u001b[00;48;2;240;30;90m240|030|090 \u001b[00m\u001b[00;48;2;240;30;120m240|030|120 \u001b[00m\u001b[00;48;2;240;30;150m240|030|150 \u001b[00m\u001b[00;48;2;240;30;180m240|030|180 \u001b[00m\u001b[00;48;2;240;30;210m240|030|210 \u001b[00m\u001b[00;48;2;240;30;240m240|030|240 \u001b[00m\n", + "\u001b[00;48;2;240;60;0m240|060|000 \u001b[00m\u001b[00;48;2;240;60;30m240|060|030 \u001b[00m\u001b[00;48;2;240;60;60m240|060|060 \u001b[00m\u001b[00;48;2;240;60;90m240|060|090 \u001b[00m\u001b[00;48;2;240;60;120m240|060|120 \u001b[00m\u001b[00;48;2;240;60;150m240|060|150 \u001b[00m\u001b[00;48;2;240;60;180m240|060|180 \u001b[00m\u001b[00;48;2;240;60;210m240|060|210 \u001b[00m\u001b[00;48;2;240;60;240m240|060|240 \u001b[00m\n", + "\u001b[00;48;2;240;90;0m240|090|000 \u001b[00m\u001b[00;48;2;240;90;30m240|090|030 \u001b[00m\u001b[00;48;2;240;90;60m240|090|060 \u001b[00m\u001b[00;48;2;240;90;90m240|090|090 \u001b[00m\u001b[00;48;2;240;90;120m240|090|120 \u001b[00m\u001b[00;48;2;240;90;150m240|090|150 \u001b[00m\u001b[00;48;2;240;90;180m240|090|180 \u001b[00m\u001b[00;48;2;240;90;210m240|090|210 \u001b[00m\u001b[00;48;2;240;90;240m240|090|240 \u001b[00m\n", + "\u001b[00;48;2;240;120;0m240|120|000 \u001b[00m\u001b[00;48;2;240;120;30m240|120|030 \u001b[00m\u001b[00;48;2;240;120;60m240|120|060 \u001b[00m\u001b[00;48;2;240;120;90m240|120|090 \u001b[00m\u001b[00;48;2;240;120;120m240|120|120 \u001b[00m\u001b[00;48;2;240;120;150m240|120|150 \u001b[00m\u001b[00;48;2;240;120;180m240|120|180 \u001b[00m\u001b[00;48;2;240;120;210m240|120|210 \u001b[00m\u001b[00;48;2;240;120;240m240|120|240 \u001b[00m\n", + "\u001b[00;48;2;240;150;0m240|150|000 \u001b[00m\u001b[00;48;2;240;150;30m240|150|030 \u001b[00m\u001b[00;48;2;240;150;60m240|150|060 \u001b[00m\u001b[00;48;2;240;150;90m240|150|090 \u001b[00m\u001b[00;48;2;240;150;120m240|150|120 \u001b[00m\u001b[00;48;2;240;150;150m240|150|150 \u001b[00m\u001b[00;48;2;240;150;180m240|150|180 \u001b[00m\u001b[00;48;2;240;150;210m240|150|210 \u001b[00m\u001b[00;48;2;240;150;240m240|150|240 \u001b[00m\n", + "\u001b[00;48;2;240;180;0m240|180|000 \u001b[00m\u001b[00;48;2;240;180;30m240|180|030 \u001b[00m\u001b[00;48;2;240;180;60m240|180|060 \u001b[00m\u001b[00;48;2;240;180;90m240|180|090 \u001b[00m\u001b[00;48;2;240;180;120m240|180|120 \u001b[00m\u001b[00;48;2;240;180;150m240|180|150 \u001b[00m\u001b[00;48;2;240;180;180m240|180|180 \u001b[00m\u001b[00;48;2;240;180;210m240|180|210 \u001b[00m\u001b[00;48;2;240;180;240m240|180|240 \u001b[00m\n", + "\u001b[00;48;2;240;210;0m240|210|000 \u001b[00m\u001b[00;48;2;240;210;30m240|210|030 \u001b[00m\u001b[00;48;2;240;210;60m240|210|060 \u001b[00m\u001b[00;48;2;240;210;90m240|210|090 \u001b[00m\u001b[00;48;2;240;210;120m240|210|120 \u001b[00m\u001b[00;48;2;240;210;150m240|210|150 \u001b[00m\u001b[00;48;2;240;210;180m240|210|180 \u001b[00m\u001b[00;48;2;240;210;210m240|210|210 \u001b[00m\u001b[00;48;2;240;210;240m240|210|240 \u001b[00m\n", + "\u001b[00;48;2;240;240;0m240|240|000 \u001b[00m\u001b[00;48;2;240;240;30m240|240|030 \u001b[00m\u001b[00;48;2;240;240;60m240|240|060 \u001b[00m\u001b[00;48;2;240;240;90m240|240|090 \u001b[00m\u001b[00;48;2;240;240;120m240|240|120 \u001b[00m\u001b[00;48;2;240;240;150m240|240|150 \u001b[00m\u001b[00;48;2;240;240;180m240|240|180 \u001b[00m\u001b[00;48;2;240;240;210m240|240|210 \u001b[00m\u001b[00;48;2;240;240;240m240|240|240 \u001b[00m\n", + "\n" ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "steps = range(0,256,30)\n", - "\n", - "t = \"{ESC}00;48;2;{r};{g};{b}m{r:03}|{g:03}|{b:03} {RESET}\"\n", - "for r in steps:\n", - " for g in steps:\n", - " for b in steps:\n", - " print (t.format(**locals()), end='')\n", - " print()\n", - " print()\n" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\u001b[00;48;2;0;0;0m000|000|000 \u001b[00m\u001b[00;48;2;0;0;30m000|000|030 \u001b[00m\u001b[00;48;2;0;0;60m000|000|060 \u001b[00m\u001b[00;48;2;0;0;90m000|000|090 \u001b[00m\u001b[00;48;2;0;0;120m000|000|120 \u001b[00m\u001b[00;48;2;0;0;150m000|000|150 \u001b[00m\u001b[00;48;2;0;0;180m000|000|180 \u001b[00m\u001b[00;48;2;0;0;210m000|000|210 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\u001b[00m\u001b[00;48;2;60;30;90m060|030|090 \u001b[00m\u001b[00;48;2;60;30;120m060|030|120 \u001b[00m\u001b[00;48;2;60;30;150m060|030|150 \u001b[00m\u001b[00;48;2;60;30;180m060|030|180 \u001b[00m\u001b[00;48;2;60;30;210m060|030|210 \u001b[00m\u001b[00;48;2;60;30;240m060|030|240 \u001b[00m\n", - "\u001b[00;48;2;60;60;0m060|060|000 \u001b[00m\u001b[00;48;2;60;60;30m060|060|030 \u001b[00m\u001b[00;48;2;60;60;60m060|060|060 \u001b[00m\u001b[00;48;2;60;60;90m060|060|090 \u001b[00m\u001b[00;48;2;60;60;120m060|060|120 \u001b[00m\u001b[00;48;2;60;60;150m060|060|150 \u001b[00m\u001b[00;48;2;60;60;180m060|060|180 \u001b[00m\u001b[00;48;2;60;60;210m060|060|210 \u001b[00m\u001b[00;48;2;60;60;240m060|060|240 \u001b[00m\n", - "\u001b[00;48;2;60;90;0m060|090|000 \u001b[00m\u001b[00;48;2;60;90;30m060|090|030 \u001b[00m\u001b[00;48;2;60;90;60m060|090|060 \u001b[00m\u001b[00;48;2;60;90;90m060|090|090 \u001b[00m\u001b[00;48;2;60;90;120m060|090|120 \u001b[00m\u001b[00;48;2;60;90;150m060|090|150 \u001b[00m\u001b[00;48;2;60;90;180m060|090|180 \u001b[00m\u001b[00;48;2;60;90;210m060|090|210 \u001b[00m\u001b[00;48;2;60;90;240m060|090|240 \u001b[00m\n", - "\u001b[00;48;2;60;120;0m060|120|000 \u001b[00m\u001b[00;48;2;60;120;30m060|120|030 \u001b[00m\u001b[00;48;2;60;120;60m060|120|060 \u001b[00m\u001b[00;48;2;60;120;90m060|120|090 \u001b[00m\u001b[00;48;2;60;120;120m060|120|120 \u001b[00m\u001b[00;48;2;60;120;150m060|120|150 \u001b[00m\u001b[00;48;2;60;120;180m060|120|180 \u001b[00m\u001b[00;48;2;60;120;210m060|120|210 \u001b[00m\u001b[00;48;2;60;120;240m060|120|240 \u001b[00m\n", - "\u001b[00;48;2;60;150;0m060|150|000 \u001b[00m\u001b[00;48;2;60;150;30m060|150|030 \u001b[00m\u001b[00;48;2;60;150;60m060|150|060 \u001b[00m\u001b[00;48;2;60;150;90m060|150|090 \u001b[00m\u001b[00;48;2;60;150;120m060|150|120 \u001b[00m\u001b[00;48;2;60;150;150m060|150|150 \u001b[00m\u001b[00;48;2;60;150;180m060|150|180 \u001b[00m\u001b[00;48;2;60;150;210m060|150|210 \u001b[00m\u001b[00;48;2;60;150;240m060|150|240 \u001b[00m\n", - "\u001b[00;48;2;60;180;0m060|180|000 \u001b[00m\u001b[00;48;2;60;180;30m060|180|030 \u001b[00m\u001b[00;48;2;60;180;60m060|180|060 \u001b[00m\u001b[00;48;2;60;180;90m060|180|090 \u001b[00m\u001b[00;48;2;60;180;120m060|180|120 \u001b[00m\u001b[00;48;2;60;180;150m060|180|150 \u001b[00m\u001b[00;48;2;60;180;180m060|180|180 \u001b[00m\u001b[00;48;2;60;180;210m060|180|210 \u001b[00m\u001b[00;48;2;60;180;240m060|180|240 \u001b[00m\n", - "\u001b[00;48;2;60;210;0m060|210|000 \u001b[00m\u001b[00;48;2;60;210;30m060|210|030 \u001b[00m\u001b[00;48;2;60;210;60m060|210|060 \u001b[00m\u001b[00;48;2;60;210;90m060|210|090 \u001b[00m\u001b[00;48;2;60;210;120m060|210|120 \u001b[00m\u001b[00;48;2;60;210;150m060|210|150 \u001b[00m\u001b[00;48;2;60;210;180m060|210|180 \u001b[00m\u001b[00;48;2;60;210;210m060|210|210 \u001b[00m\u001b[00;48;2;60;210;240m060|210|240 \u001b[00m\n", - "\u001b[00;48;2;60;240;0m060|240|000 \u001b[00m\u001b[00;48;2;60;240;30m060|240|030 \u001b[00m\u001b[00;48;2;60;240;60m060|240|060 \u001b[00m\u001b[00;48;2;60;240;90m060|240|090 \u001b[00m\u001b[00;48;2;60;240;120m060|240|120 \u001b[00m\u001b[00;48;2;60;240;150m060|240|150 \u001b[00m\u001b[00;48;2;60;240;180m060|240|180 \u001b[00m\u001b[00;48;2;60;240;210m060|240|210 \u001b[00m\u001b[00;48;2;60;240;240m060|240|240 \u001b[00m\n", - "\n", - "\u001b[00;48;2;90;0;0m090|000|000 \u001b[00m\u001b[00;48;2;90;0;30m090|000|030 \u001b[00m\u001b[00;48;2;90;0;60m090|000|060 \u001b[00m\u001b[00;48;2;90;0;90m090|000|090 \u001b[00m\u001b[00;48;2;90;0;120m090|000|120 \u001b[00m\u001b[00;48;2;90;0;150m090|000|150 \u001b[00m\u001b[00;48;2;90;0;180m090|000|180 \u001b[00m\u001b[00;48;2;90;0;210m090|000|210 \u001b[00m\u001b[00;48;2;90;0;240m090|000|240 \u001b[00m\n", - "\u001b[00;48;2;90;30;0m090|030|000 \u001b[00m\u001b[00;48;2;90;30;30m090|030|030 \u001b[00m\u001b[00;48;2;90;30;60m090|030|060 \u001b[00m\u001b[00;48;2;90;30;90m090|030|090 \u001b[00m\u001b[00;48;2;90;30;120m090|030|120 \u001b[00m\u001b[00;48;2;90;30;150m090|030|150 \u001b[00m\u001b[00;48;2;90;30;180m090|030|180 \u001b[00m\u001b[00;48;2;90;30;210m090|030|210 \u001b[00m\u001b[00;48;2;90;30;240m090|030|240 \u001b[00m\n", - "\u001b[00;48;2;90;60;0m090|060|000 \u001b[00m\u001b[00;48;2;90;60;30m090|060|030 \u001b[00m\u001b[00;48;2;90;60;60m090|060|060 \u001b[00m\u001b[00;48;2;90;60;90m090|060|090 \u001b[00m\u001b[00;48;2;90;60;120m090|060|120 \u001b[00m\u001b[00;48;2;90;60;150m090|060|150 \u001b[00m\u001b[00;48;2;90;60;180m090|060|180 \u001b[00m\u001b[00;48;2;90;60;210m090|060|210 \u001b[00m\u001b[00;48;2;90;60;240m090|060|240 \u001b[00m\n", - "\u001b[00;48;2;90;90;0m090|090|000 \u001b[00m\u001b[00;48;2;90;90;30m090|090|030 \u001b[00m\u001b[00;48;2;90;90;60m090|090|060 \u001b[00m\u001b[00;48;2;90;90;90m090|090|090 \u001b[00m\u001b[00;48;2;90;90;120m090|090|120 \u001b[00m\u001b[00;48;2;90;90;150m090|090|150 \u001b[00m\u001b[00;48;2;90;90;180m090|090|180 \u001b[00m\u001b[00;48;2;90;90;210m090|090|210 \u001b[00m\u001b[00;48;2;90;90;240m090|090|240 \u001b[00m\n", - "\u001b[00;48;2;90;120;0m090|120|000 \u001b[00m\u001b[00;48;2;90;120;30m090|120|030 \u001b[00m\u001b[00;48;2;90;120;60m090|120|060 \u001b[00m\u001b[00;48;2;90;120;90m090|120|090 \u001b[00m\u001b[00;48;2;90;120;120m090|120|120 \u001b[00m\u001b[00;48;2;90;120;150m090|120|150 \u001b[00m\u001b[00;48;2;90;120;180m090|120|180 \u001b[00m\u001b[00;48;2;90;120;210m090|120|210 \u001b[00m\u001b[00;48;2;90;120;240m090|120|240 \u001b[00m\n", - "\u001b[00;48;2;90;150;0m090|150|000 \u001b[00m\u001b[00;48;2;90;150;30m090|150|030 \u001b[00m\u001b[00;48;2;90;150;60m090|150|060 \u001b[00m\u001b[00;48;2;90;150;90m090|150|090 \u001b[00m\u001b[00;48;2;90;150;120m090|150|120 \u001b[00m\u001b[00;48;2;90;150;150m090|150|150 \u001b[00m\u001b[00;48;2;90;150;180m090|150|180 \u001b[00m\u001b[00;48;2;90;150;210m090|150|210 \u001b[00m\u001b[00;48;2;90;150;240m090|150|240 \u001b[00m\n", - "\u001b[00;48;2;90;180;0m090|180|000 \u001b[00m\u001b[00;48;2;90;180;30m090|180|030 \u001b[00m\u001b[00;48;2;90;180;60m090|180|060 \u001b[00m\u001b[00;48;2;90;180;90m090|180|090 \u001b[00m\u001b[00;48;2;90;180;120m090|180|120 \u001b[00m\u001b[00;48;2;90;180;150m090|180|150 \u001b[00m\u001b[00;48;2;90;180;180m090|180|180 \u001b[00m\u001b[00;48;2;90;180;210m090|180|210 \u001b[00m\u001b[00;48;2;90;180;240m090|180|240 \u001b[00m\n", - "\u001b[00;48;2;90;210;0m090|210|000 \u001b[00m\u001b[00;48;2;90;210;30m090|210|030 \u001b[00m\u001b[00;48;2;90;210;60m090|210|060 \u001b[00m\u001b[00;48;2;90;210;90m090|210|090 \u001b[00m\u001b[00;48;2;90;210;120m090|210|120 \u001b[00m\u001b[00;48;2;90;210;150m090|210|150 \u001b[00m\u001b[00;48;2;90;210;180m090|210|180 \u001b[00m\u001b[00;48;2;90;210;210m090|210|210 \u001b[00m\u001b[00;48;2;90;210;240m090|210|240 \u001b[00m\n", - "\u001b[00;48;2;90;240;0m090|240|000 \u001b[00m\u001b[00;48;2;90;240;30m090|240|030 \u001b[00m\u001b[00;48;2;90;240;60m090|240|060 \u001b[00m\u001b[00;48;2;90;240;90m090|240|090 \u001b[00m\u001b[00;48;2;90;240;120m090|240|120 \u001b[00m\u001b[00;48;2;90;240;150m090|240|150 \u001b[00m\u001b[00;48;2;90;240;180m090|240|180 \u001b[00m\u001b[00;48;2;90;240;210m090|240|210 \u001b[00m\u001b[00;48;2;90;240;240m090|240|240 \u001b[00m\n", - "\n", - "\u001b[00;48;2;120;0;0m120|000|000 \u001b[00m\u001b[00;48;2;120;0;30m120|000|030 \u001b[00m\u001b[00;48;2;120;0;60m120|000|060 \u001b[00m\u001b[00;48;2;120;0;90m120|000|090 \u001b[00m\u001b[00;48;2;120;0;120m120|000|120 \u001b[00m\u001b[00;48;2;120;0;150m120|000|150 \u001b[00m\u001b[00;48;2;120;0;180m120|000|180 \u001b[00m\u001b[00;48;2;120;0;210m120|000|210 \u001b[00m\u001b[00;48;2;120;0;240m120|000|240 \u001b[00m\n", - "\u001b[00;48;2;120;30;0m120|030|000 \u001b[00m\u001b[00;48;2;120;30;30m120|030|030 \u001b[00m\u001b[00;48;2;120;30;60m120|030|060 \u001b[00m\u001b[00;48;2;120;30;90m120|030|090 \u001b[00m\u001b[00;48;2;120;30;120m120|030|120 \u001b[00m\u001b[00;48;2;120;30;150m120|030|150 \u001b[00m\u001b[00;48;2;120;30;180m120|030|180 \u001b[00m\u001b[00;48;2;120;30;210m120|030|210 \u001b[00m\u001b[00;48;2;120;30;240m120|030|240 \u001b[00m\n", - "\u001b[00;48;2;120;60;0m120|060|000 \u001b[00m\u001b[00;48;2;120;60;30m120|060|030 \u001b[00m\u001b[00;48;2;120;60;60m120|060|060 \u001b[00m\u001b[00;48;2;120;60;90m120|060|090 \u001b[00m\u001b[00;48;2;120;60;120m120|060|120 \u001b[00m\u001b[00;48;2;120;60;150m120|060|150 \u001b[00m\u001b[00;48;2;120;60;180m120|060|180 \u001b[00m\u001b[00;48;2;120;60;210m120|060|210 \u001b[00m\u001b[00;48;2;120;60;240m120|060|240 \u001b[00m\n", - "\u001b[00;48;2;120;90;0m120|090|000 \u001b[00m\u001b[00;48;2;120;90;30m120|090|030 \u001b[00m\u001b[00;48;2;120;90;60m120|090|060 \u001b[00m\u001b[00;48;2;120;90;90m120|090|090 \u001b[00m\u001b[00;48;2;120;90;120m120|090|120 \u001b[00m\u001b[00;48;2;120;90;150m120|090|150 \u001b[00m\u001b[00;48;2;120;90;180m120|090|180 \u001b[00m\u001b[00;48;2;120;90;210m120|090|210 \u001b[00m\u001b[00;48;2;120;90;240m120|090|240 \u001b[00m\n", - "\u001b[00;48;2;120;120;0m120|120|000 \u001b[00m\u001b[00;48;2;120;120;30m120|120|030 \u001b[00m\u001b[00;48;2;120;120;60m120|120|060 \u001b[00m\u001b[00;48;2;120;120;90m120|120|090 \u001b[00m\u001b[00;48;2;120;120;120m120|120|120 \u001b[00m\u001b[00;48;2;120;120;150m120|120|150 \u001b[00m\u001b[00;48;2;120;120;180m120|120|180 \u001b[00m\u001b[00;48;2;120;120;210m120|120|210 \u001b[00m\u001b[00;48;2;120;120;240m120|120|240 \u001b[00m\n", - "\u001b[00;48;2;120;150;0m120|150|000 \u001b[00m\u001b[00;48;2;120;150;30m120|150|030 \u001b[00m\u001b[00;48;2;120;150;60m120|150|060 \u001b[00m\u001b[00;48;2;120;150;90m120|150|090 \u001b[00m\u001b[00;48;2;120;150;120m120|150|120 \u001b[00m\u001b[00;48;2;120;150;150m120|150|150 \u001b[00m\u001b[00;48;2;120;150;180m120|150|180 \u001b[00m\u001b[00;48;2;120;150;210m120|150|210 \u001b[00m\u001b[00;48;2;120;150;240m120|150|240 \u001b[00m\n", - "\u001b[00;48;2;120;180;0m120|180|000 \u001b[00m\u001b[00;48;2;120;180;30m120|180|030 \u001b[00m\u001b[00;48;2;120;180;60m120|180|060 \u001b[00m\u001b[00;48;2;120;180;90m120|180|090 \u001b[00m\u001b[00;48;2;120;180;120m120|180|120 \u001b[00m\u001b[00;48;2;120;180;150m120|180|150 \u001b[00m\u001b[00;48;2;120;180;180m120|180|180 \u001b[00m\u001b[00;48;2;120;180;210m120|180|210 \u001b[00m\u001b[00;48;2;120;180;240m120|180|240 \u001b[00m\n", - "\u001b[00;48;2;120;210;0m120|210|000 \u001b[00m\u001b[00;48;2;120;210;30m120|210|030 \u001b[00m\u001b[00;48;2;120;210;60m120|210|060 \u001b[00m\u001b[00;48;2;120;210;90m120|210|090 \u001b[00m\u001b[00;48;2;120;210;120m120|210|120 \u001b[00m\u001b[00;48;2;120;210;150m120|210|150 \u001b[00m\u001b[00;48;2;120;210;180m120|210|180 \u001b[00m\u001b[00;48;2;120;210;210m120|210|210 \u001b[00m\u001b[00;48;2;120;210;240m120|210|240 \u001b[00m\n", - "\u001b[00;48;2;120;240;0m120|240|000 \u001b[00m\u001b[00;48;2;120;240;30m120|240|030 \u001b[00m\u001b[00;48;2;120;240;60m120|240|060 \u001b[00m\u001b[00;48;2;120;240;90m120|240|090 \u001b[00m\u001b[00;48;2;120;240;120m120|240|120 \u001b[00m\u001b[00;48;2;120;240;150m120|240|150 \u001b[00m\u001b[00;48;2;120;240;180m120|240|180 \u001b[00m\u001b[00;48;2;120;240;210m120|240|210 \u001b[00m\u001b[00;48;2;120;240;240m120|240|240 \u001b[00m\n", - "\n", - "\u001b[00;48;2;150;0;0m150|000|000 \u001b[00m\u001b[00;48;2;150;0;30m150|000|030 \u001b[00m\u001b[00;48;2;150;0;60m150|000|060 \u001b[00m\u001b[00;48;2;150;0;90m150|000|090 \u001b[00m\u001b[00;48;2;150;0;120m150|000|120 \u001b[00m\u001b[00;48;2;150;0;150m150|000|150 \u001b[00m\u001b[00;48;2;150;0;180m150|000|180 \u001b[00m\u001b[00;48;2;150;0;210m150|000|210 \u001b[00m\u001b[00;48;2;150;0;240m150|000|240 \u001b[00m\n", - "\u001b[00;48;2;150;30;0m150|030|000 \u001b[00m\u001b[00;48;2;150;30;30m150|030|030 \u001b[00m\u001b[00;48;2;150;30;60m150|030|060 \u001b[00m\u001b[00;48;2;150;30;90m150|030|090 \u001b[00m\u001b[00;48;2;150;30;120m150|030|120 \u001b[00m\u001b[00;48;2;150;30;150m150|030|150 \u001b[00m\u001b[00;48;2;150;30;180m150|030|180 \u001b[00m\u001b[00;48;2;150;30;210m150|030|210 \u001b[00m\u001b[00;48;2;150;30;240m150|030|240 \u001b[00m\n", - "\u001b[00;48;2;150;60;0m150|060|000 \u001b[00m\u001b[00;48;2;150;60;30m150|060|030 \u001b[00m\u001b[00;48;2;150;60;60m150|060|060 \u001b[00m\u001b[00;48;2;150;60;90m150|060|090 \u001b[00m\u001b[00;48;2;150;60;120m150|060|120 \u001b[00m\u001b[00;48;2;150;60;150m150|060|150 \u001b[00m\u001b[00;48;2;150;60;180m150|060|180 \u001b[00m\u001b[00;48;2;150;60;210m150|060|210 \u001b[00m\u001b[00;48;2;150;60;240m150|060|240 \u001b[00m\n", - "\u001b[00;48;2;150;90;0m150|090|000 \u001b[00m\u001b[00;48;2;150;90;30m150|090|030 \u001b[00m\u001b[00;48;2;150;90;60m150|090|060 \u001b[00m\u001b[00;48;2;150;90;90m150|090|090 \u001b[00m\u001b[00;48;2;150;90;120m150|090|120 \u001b[00m\u001b[00;48;2;150;90;150m150|090|150 \u001b[00m\u001b[00;48;2;150;90;180m150|090|180 \u001b[00m\u001b[00;48;2;150;90;210m150|090|210 \u001b[00m\u001b[00;48;2;150;90;240m150|090|240 \u001b[00m\n", - "\u001b[00;48;2;150;120;0m150|120|000 \u001b[00m\u001b[00;48;2;150;120;30m150|120|030 \u001b[00m\u001b[00;48;2;150;120;60m150|120|060 \u001b[00m\u001b[00;48;2;150;120;90m150|120|090 \u001b[00m\u001b[00;48;2;150;120;120m150|120|120 \u001b[00m\u001b[00;48;2;150;120;150m150|120|150 \u001b[00m\u001b[00;48;2;150;120;180m150|120|180 \u001b[00m\u001b[00;48;2;150;120;210m150|120|210 \u001b[00m\u001b[00;48;2;150;120;240m150|120|240 \u001b[00m\n", - "\u001b[00;48;2;150;150;0m150|150|000 \u001b[00m\u001b[00;48;2;150;150;30m150|150|030 \u001b[00m\u001b[00;48;2;150;150;60m150|150|060 \u001b[00m\u001b[00;48;2;150;150;90m150|150|090 \u001b[00m\u001b[00;48;2;150;150;120m150|150|120 \u001b[00m\u001b[00;48;2;150;150;150m150|150|150 \u001b[00m\u001b[00;48;2;150;150;180m150|150|180 \u001b[00m\u001b[00;48;2;150;150;210m150|150|210 \u001b[00m\u001b[00;48;2;150;150;240m150|150|240 \u001b[00m\n", - "\u001b[00;48;2;150;180;0m150|180|000 \u001b[00m\u001b[00;48;2;150;180;30m150|180|030 \u001b[00m\u001b[00;48;2;150;180;60m150|180|060 \u001b[00m\u001b[00;48;2;150;180;90m150|180|090 \u001b[00m\u001b[00;48;2;150;180;120m150|180|120 \u001b[00m\u001b[00;48;2;150;180;150m150|180|150 \u001b[00m\u001b[00;48;2;150;180;180m150|180|180 \u001b[00m\u001b[00;48;2;150;180;210m150|180|210 \u001b[00m\u001b[00;48;2;150;180;240m150|180|240 \u001b[00m\n", - "\u001b[00;48;2;150;210;0m150|210|000 \u001b[00m\u001b[00;48;2;150;210;30m150|210|030 \u001b[00m\u001b[00;48;2;150;210;60m150|210|060 \u001b[00m\u001b[00;48;2;150;210;90m150|210|090 \u001b[00m\u001b[00;48;2;150;210;120m150|210|120 \u001b[00m\u001b[00;48;2;150;210;150m150|210|150 \u001b[00m\u001b[00;48;2;150;210;180m150|210|180 \u001b[00m\u001b[00;48;2;150;210;210m150|210|210 \u001b[00m\u001b[00;48;2;150;210;240m150|210|240 \u001b[00m\n", - "\u001b[00;48;2;150;240;0m150|240|000 \u001b[00m\u001b[00;48;2;150;240;30m150|240|030 \u001b[00m\u001b[00;48;2;150;240;60m150|240|060 \u001b[00m\u001b[00;48;2;150;240;90m150|240|090 \u001b[00m\u001b[00;48;2;150;240;120m150|240|120 \u001b[00m\u001b[00;48;2;150;240;150m150|240|150 \u001b[00m\u001b[00;48;2;150;240;180m150|240|180 \u001b[00m\u001b[00;48;2;150;240;210m150|240|210 \u001b[00m\u001b[00;48;2;150;240;240m150|240|240 \u001b[00m\n", - "\n", - "\u001b[00;48;2;180;0;0m180|000|000 \u001b[00m\u001b[00;48;2;180;0;30m180|000|030 \u001b[00m\u001b[00;48;2;180;0;60m180|000|060 \u001b[00m\u001b[00;48;2;180;0;90m180|000|090 \u001b[00m\u001b[00;48;2;180;0;120m180|000|120 \u001b[00m\u001b[00;48;2;180;0;150m180|000|150 \u001b[00m\u001b[00;48;2;180;0;180m180|000|180 \u001b[00m\u001b[00;48;2;180;0;210m180|000|210 \u001b[00m\u001b[00;48;2;180;0;240m180|000|240 \u001b[00m\n", - "\u001b[00;48;2;180;30;0m180|030|000 \u001b[00m\u001b[00;48;2;180;30;30m180|030|030 \u001b[00m\u001b[00;48;2;180;30;60m180|030|060 \u001b[00m\u001b[00;48;2;180;30;90m180|030|090 \u001b[00m\u001b[00;48;2;180;30;120m180|030|120 \u001b[00m\u001b[00;48;2;180;30;150m180|030|150 \u001b[00m\u001b[00;48;2;180;30;180m180|030|180 \u001b[00m\u001b[00;48;2;180;30;210m180|030|210 \u001b[00m\u001b[00;48;2;180;30;240m180|030|240 \u001b[00m\n", - "\u001b[00;48;2;180;60;0m180|060|000 \u001b[00m\u001b[00;48;2;180;60;30m180|060|030 \u001b[00m\u001b[00;48;2;180;60;60m180|060|060 \u001b[00m\u001b[00;48;2;180;60;90m180|060|090 \u001b[00m\u001b[00;48;2;180;60;120m180|060|120 \u001b[00m\u001b[00;48;2;180;60;150m180|060|150 \u001b[00m\u001b[00;48;2;180;60;180m180|060|180 \u001b[00m\u001b[00;48;2;180;60;210m180|060|210 \u001b[00m\u001b[00;48;2;180;60;240m180|060|240 \u001b[00m\n", - "\u001b[00;48;2;180;90;0m180|090|000 \u001b[00m\u001b[00;48;2;180;90;30m180|090|030 \u001b[00m\u001b[00;48;2;180;90;60m180|090|060 \u001b[00m\u001b[00;48;2;180;90;90m180|090|090 \u001b[00m\u001b[00;48;2;180;90;120m180|090|120 \u001b[00m\u001b[00;48;2;180;90;150m180|090|150 \u001b[00m\u001b[00;48;2;180;90;180m180|090|180 \u001b[00m\u001b[00;48;2;180;90;210m180|090|210 \u001b[00m\u001b[00;48;2;180;90;240m180|090|240 \u001b[00m\n", - "\u001b[00;48;2;180;120;0m180|120|000 \u001b[00m\u001b[00;48;2;180;120;30m180|120|030 \u001b[00m\u001b[00;48;2;180;120;60m180|120|060 \u001b[00m\u001b[00;48;2;180;120;90m180|120|090 \u001b[00m\u001b[00;48;2;180;120;120m180|120|120 \u001b[00m\u001b[00;48;2;180;120;150m180|120|150 \u001b[00m\u001b[00;48;2;180;120;180m180|120|180 \u001b[00m\u001b[00;48;2;180;120;210m180|120|210 \u001b[00m\u001b[00;48;2;180;120;240m180|120|240 \u001b[00m\n", - "\u001b[00;48;2;180;150;0m180|150|000 \u001b[00m\u001b[00;48;2;180;150;30m180|150|030 \u001b[00m\u001b[00;48;2;180;150;60m180|150|060 \u001b[00m\u001b[00;48;2;180;150;90m180|150|090 \u001b[00m\u001b[00;48;2;180;150;120m180|150|120 \u001b[00m\u001b[00;48;2;180;150;150m180|150|150 \u001b[00m\u001b[00;48;2;180;150;180m180|150|180 \u001b[00m\u001b[00;48;2;180;150;210m180|150|210 \u001b[00m\u001b[00;48;2;180;150;240m180|150|240 \u001b[00m\n", - "\u001b[00;48;2;180;180;0m180|180|000 \u001b[00m\u001b[00;48;2;180;180;30m180|180|030 \u001b[00m\u001b[00;48;2;180;180;60m180|180|060 \u001b[00m\u001b[00;48;2;180;180;90m180|180|090 \u001b[00m\u001b[00;48;2;180;180;120m180|180|120 \u001b[00m\u001b[00;48;2;180;180;150m180|180|150 \u001b[00m\u001b[00;48;2;180;180;180m180|180|180 \u001b[00m\u001b[00;48;2;180;180;210m180|180|210 \u001b[00m\u001b[00;48;2;180;180;240m180|180|240 \u001b[00m\n", - "\u001b[00;48;2;180;210;0m180|210|000 \u001b[00m\u001b[00;48;2;180;210;30m180|210|030 \u001b[00m\u001b[00;48;2;180;210;60m180|210|060 \u001b[00m\u001b[00;48;2;180;210;90m180|210|090 \u001b[00m\u001b[00;48;2;180;210;120m180|210|120 \u001b[00m\u001b[00;48;2;180;210;150m180|210|150 \u001b[00m\u001b[00;48;2;180;210;180m180|210|180 \u001b[00m\u001b[00;48;2;180;210;210m180|210|210 \u001b[00m\u001b[00;48;2;180;210;240m180|210|240 \u001b[00m\n", - "\u001b[00;48;2;180;240;0m180|240|000 \u001b[00m\u001b[00;48;2;180;240;30m180|240|030 \u001b[00m\u001b[00;48;2;180;240;60m180|240|060 \u001b[00m\u001b[00;48;2;180;240;90m180|240|090 \u001b[00m\u001b[00;48;2;180;240;120m180|240|120 \u001b[00m\u001b[00;48;2;180;240;150m180|240|150 \u001b[00m\u001b[00;48;2;180;240;180m180|240|180 \u001b[00m\u001b[00;48;2;180;240;210m180|240|210 \u001b[00m\u001b[00;48;2;180;240;240m180|240|240 \u001b[00m\n", - "\n", - "\u001b[00;48;2;210;0;0m210|000|000 \u001b[00m\u001b[00;48;2;210;0;30m210|000|030 \u001b[00m\u001b[00;48;2;210;0;60m210|000|060 \u001b[00m\u001b[00;48;2;210;0;90m210|000|090 \u001b[00m\u001b[00;48;2;210;0;120m210|000|120 \u001b[00m\u001b[00;48;2;210;0;150m210|000|150 \u001b[00m\u001b[00;48;2;210;0;180m210|000|180 \u001b[00m\u001b[00;48;2;210;0;210m210|000|210 \u001b[00m\u001b[00;48;2;210;0;240m210|000|240 \u001b[00m\n", - "\u001b[00;48;2;210;30;0m210|030|000 \u001b[00m\u001b[00;48;2;210;30;30m210|030|030 \u001b[00m\u001b[00;48;2;210;30;60m210|030|060 \u001b[00m\u001b[00;48;2;210;30;90m210|030|090 \u001b[00m\u001b[00;48;2;210;30;120m210|030|120 \u001b[00m\u001b[00;48;2;210;30;150m210|030|150 \u001b[00m\u001b[00;48;2;210;30;180m210|030|180 \u001b[00m\u001b[00;48;2;210;30;210m210|030|210 \u001b[00m\u001b[00;48;2;210;30;240m210|030|240 \u001b[00m\n", - "\u001b[00;48;2;210;60;0m210|060|000 \u001b[00m\u001b[00;48;2;210;60;30m210|060|030 \u001b[00m\u001b[00;48;2;210;60;60m210|060|060 \u001b[00m\u001b[00;48;2;210;60;90m210|060|090 \u001b[00m\u001b[00;48;2;210;60;120m210|060|120 \u001b[00m\u001b[00;48;2;210;60;150m210|060|150 \u001b[00m\u001b[00;48;2;210;60;180m210|060|180 \u001b[00m\u001b[00;48;2;210;60;210m210|060|210 \u001b[00m\u001b[00;48;2;210;60;240m210|060|240 \u001b[00m\n", - "\u001b[00;48;2;210;90;0m210|090|000 \u001b[00m\u001b[00;48;2;210;90;30m210|090|030 \u001b[00m\u001b[00;48;2;210;90;60m210|090|060 \u001b[00m\u001b[00;48;2;210;90;90m210|090|090 \u001b[00m\u001b[00;48;2;210;90;120m210|090|120 \u001b[00m\u001b[00;48;2;210;90;150m210|090|150 \u001b[00m\u001b[00;48;2;210;90;180m210|090|180 \u001b[00m\u001b[00;48;2;210;90;210m210|090|210 \u001b[00m\u001b[00;48;2;210;90;240m210|090|240 \u001b[00m\n", - "\u001b[00;48;2;210;120;0m210|120|000 \u001b[00m\u001b[00;48;2;210;120;30m210|120|030 \u001b[00m\u001b[00;48;2;210;120;60m210|120|060 \u001b[00m\u001b[00;48;2;210;120;90m210|120|090 \u001b[00m\u001b[00;48;2;210;120;120m210|120|120 \u001b[00m\u001b[00;48;2;210;120;150m210|120|150 \u001b[00m\u001b[00;48;2;210;120;180m210|120|180 \u001b[00m\u001b[00;48;2;210;120;210m210|120|210 \u001b[00m\u001b[00;48;2;210;120;240m210|120|240 \u001b[00m\n", - "\u001b[00;48;2;210;150;0m210|150|000 \u001b[00m\u001b[00;48;2;210;150;30m210|150|030 \u001b[00m\u001b[00;48;2;210;150;60m210|150|060 \u001b[00m\u001b[00;48;2;210;150;90m210|150|090 \u001b[00m\u001b[00;48;2;210;150;120m210|150|120 \u001b[00m\u001b[00;48;2;210;150;150m210|150|150 \u001b[00m\u001b[00;48;2;210;150;180m210|150|180 \u001b[00m\u001b[00;48;2;210;150;210m210|150|210 \u001b[00m\u001b[00;48;2;210;150;240m210|150|240 \u001b[00m\n", - "\u001b[00;48;2;210;180;0m210|180|000 \u001b[00m\u001b[00;48;2;210;180;30m210|180|030 \u001b[00m\u001b[00;48;2;210;180;60m210|180|060 \u001b[00m\u001b[00;48;2;210;180;90m210|180|090 \u001b[00m\u001b[00;48;2;210;180;120m210|180|120 \u001b[00m\u001b[00;48;2;210;180;150m210|180|150 \u001b[00m\u001b[00;48;2;210;180;180m210|180|180 \u001b[00m\u001b[00;48;2;210;180;210m210|180|210 \u001b[00m\u001b[00;48;2;210;180;240m210|180|240 \u001b[00m\n", - "\u001b[00;48;2;210;210;0m210|210|000 \u001b[00m\u001b[00;48;2;210;210;30m210|210|030 \u001b[00m\u001b[00;48;2;210;210;60m210|210|060 \u001b[00m\u001b[00;48;2;210;210;90m210|210|090 \u001b[00m\u001b[00;48;2;210;210;120m210|210|120 \u001b[00m\u001b[00;48;2;210;210;150m210|210|150 \u001b[00m\u001b[00;48;2;210;210;180m210|210|180 \u001b[00m\u001b[00;48;2;210;210;210m210|210|210 \u001b[00m\u001b[00;48;2;210;210;240m210|210|240 \u001b[00m\n", - "\u001b[00;48;2;210;240;0m210|240|000 \u001b[00m\u001b[00;48;2;210;240;30m210|240|030 \u001b[00m\u001b[00;48;2;210;240;60m210|240|060 \u001b[00m\u001b[00;48;2;210;240;90m210|240|090 \u001b[00m\u001b[00;48;2;210;240;120m210|240|120 \u001b[00m\u001b[00;48;2;210;240;150m210|240|150 \u001b[00m\u001b[00;48;2;210;240;180m210|240|180 \u001b[00m\u001b[00;48;2;210;240;210m210|240|210 \u001b[00m\u001b[00;48;2;210;240;240m210|240|240 \u001b[00m\n", - "\n", - "\u001b[00;48;2;240;0;0m240|000|000 \u001b[00m\u001b[00;48;2;240;0;30m240|000|030 \u001b[00m\u001b[00;48;2;240;0;60m240|000|060 \u001b[00m\u001b[00;48;2;240;0;90m240|000|090 \u001b[00m\u001b[00;48;2;240;0;120m240|000|120 \u001b[00m\u001b[00;48;2;240;0;150m240|000|150 \u001b[00m\u001b[00;48;2;240;0;180m240|000|180 \u001b[00m\u001b[00;48;2;240;0;210m240|000|210 \u001b[00m\u001b[00;48;2;240;0;240m240|000|240 \u001b[00m\n", - "\u001b[00;48;2;240;30;0m240|030|000 \u001b[00m\u001b[00;48;2;240;30;30m240|030|030 \u001b[00m\u001b[00;48;2;240;30;60m240|030|060 \u001b[00m\u001b[00;48;2;240;30;90m240|030|090 \u001b[00m\u001b[00;48;2;240;30;120m240|030|120 \u001b[00m\u001b[00;48;2;240;30;150m240|030|150 \u001b[00m\u001b[00;48;2;240;30;180m240|030|180 \u001b[00m\u001b[00;48;2;240;30;210m240|030|210 \u001b[00m\u001b[00;48;2;240;30;240m240|030|240 \u001b[00m\n", - "\u001b[00;48;2;240;60;0m240|060|000 \u001b[00m\u001b[00;48;2;240;60;30m240|060|030 \u001b[00m\u001b[00;48;2;240;60;60m240|060|060 \u001b[00m\u001b[00;48;2;240;60;90m240|060|090 \u001b[00m\u001b[00;48;2;240;60;120m240|060|120 \u001b[00m\u001b[00;48;2;240;60;150m240|060|150 \u001b[00m\u001b[00;48;2;240;60;180m240|060|180 \u001b[00m\u001b[00;48;2;240;60;210m240|060|210 \u001b[00m\u001b[00;48;2;240;60;240m240|060|240 \u001b[00m\n", - "\u001b[00;48;2;240;90;0m240|090|000 \u001b[00m\u001b[00;48;2;240;90;30m240|090|030 \u001b[00m\u001b[00;48;2;240;90;60m240|090|060 \u001b[00m\u001b[00;48;2;240;90;90m240|090|090 \u001b[00m\u001b[00;48;2;240;90;120m240|090|120 \u001b[00m\u001b[00;48;2;240;90;150m240|090|150 \u001b[00m\u001b[00;48;2;240;90;180m240|090|180 \u001b[00m\u001b[00;48;2;240;90;210m240|090|210 \u001b[00m\u001b[00;48;2;240;90;240m240|090|240 \u001b[00m\n", - "\u001b[00;48;2;240;120;0m240|120|000 \u001b[00m\u001b[00;48;2;240;120;30m240|120|030 \u001b[00m\u001b[00;48;2;240;120;60m240|120|060 \u001b[00m\u001b[00;48;2;240;120;90m240|120|090 \u001b[00m\u001b[00;48;2;240;120;120m240|120|120 \u001b[00m\u001b[00;48;2;240;120;150m240|120|150 \u001b[00m\u001b[00;48;2;240;120;180m240|120|180 \u001b[00m\u001b[00;48;2;240;120;210m240|120|210 \u001b[00m\u001b[00;48;2;240;120;240m240|120|240 \u001b[00m\n", - "\u001b[00;48;2;240;150;0m240|150|000 \u001b[00m\u001b[00;48;2;240;150;30m240|150|030 \u001b[00m\u001b[00;48;2;240;150;60m240|150|060 \u001b[00m\u001b[00;48;2;240;150;90m240|150|090 \u001b[00m\u001b[00;48;2;240;150;120m240|150|120 \u001b[00m\u001b[00;48;2;240;150;150m240|150|150 \u001b[00m\u001b[00;48;2;240;150;180m240|150|180 \u001b[00m\u001b[00;48;2;240;150;210m240|150|210 \u001b[00m\u001b[00;48;2;240;150;240m240|150|240 \u001b[00m\n", - "\u001b[00;48;2;240;180;0m240|180|000 \u001b[00m\u001b[00;48;2;240;180;30m240|180|030 \u001b[00m\u001b[00;48;2;240;180;60m240|180|060 \u001b[00m\u001b[00;48;2;240;180;90m240|180|090 \u001b[00m\u001b[00;48;2;240;180;120m240|180|120 \u001b[00m\u001b[00;48;2;240;180;150m240|180|150 \u001b[00m\u001b[00;48;2;240;180;180m240|180|180 \u001b[00m\u001b[00;48;2;240;180;210m240|180|210 \u001b[00m\u001b[00;48;2;240;180;240m240|180|240 \u001b[00m\n", - "\u001b[00;48;2;240;210;0m240|210|000 \u001b[00m\u001b[00;48;2;240;210;30m240|210|030 \u001b[00m\u001b[00;48;2;240;210;60m240|210|060 \u001b[00m\u001b[00;48;2;240;210;90m240|210|090 \u001b[00m\u001b[00;48;2;240;210;120m240|210|120 \u001b[00m\u001b[00;48;2;240;210;150m240|210|150 \u001b[00m\u001b[00;48;2;240;210;180m240|210|180 \u001b[00m\u001b[00;48;2;240;210;210m240|210|210 \u001b[00m\u001b[00;48;2;240;210;240m240|210|240 \u001b[00m\n", - "\u001b[00;48;2;240;240;0m240|240|000 \u001b[00m\u001b[00;48;2;240;240;30m240|240|030 \u001b[00m\u001b[00;48;2;240;240;60m240|240|060 \u001b[00m\u001b[00;48;2;240;240;90m240|240|090 \u001b[00m\u001b[00;48;2;240;240;120m240|240|120 \u001b[00m\u001b[00;48;2;240;240;150m240|240|150 \u001b[00m\u001b[00;48;2;240;240;180m240|240|180 \u001b[00m\u001b[00;48;2;240;240;210m240|240|210 \u001b[00m\u001b[00;48;2;240;240;240m240|240|240 \u001b[00m\n", - "\n" - ] - } - ], - "prompt_number": 47 } ], - "metadata": {} + "source": [ + "steps = range(0,256,30)\n", + "\n", + "t = \"{ESC}00;48;2;{r};{g};{b}m{r:03}|{g:03}|{b:03} {RESET}\"\n", + "for r in steps:\n", + " for g in steps:\n", + " for b in steps:\n", + " print (t.format(**locals()), end='')\n", + " print()\n", + " print()\n" + ] + } + ], + "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": "3.4.2" } - ] -} \ No newline at end of file + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/tools/tests/CSS Reference.ipynb b/tools/tests/CSS Reference.ipynb index c7fa036..b1df3f9 100644 --- a/tools/tests/CSS Reference.ipynb +++ b/tools/tests/CSS Reference.ipynb @@ -1,495 +1,8193 @@ { - "metadata": { - "name": "All Css" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ + "cells": [ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "

CSS Playground

" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "A notebook that contain most of the things that could be displayed, to test CSS, feel free to add things to it, and send modification" - ] - }, - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Title first level" - ] - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "Title second Level" - ] - }, - { - "cell_type": "heading", - "level": 3, - "metadata": {}, - "source": [ - "Title third level" - ] - }, - { - "cell_type": "heading", - "level": 4, - "metadata": {}, - "source": [ - "h4" - ] - }, - { - "cell_type": "heading", - "level": 5, - "metadata": {}, - "source": [ - "h5" - ] - }, - { - "cell_type": "heading", - "level": 6, - "metadata": {}, - "source": [ - "h6" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# h1\n", - "## h2\n", - "### h3\n", - "#### h4\n", - "##### h6\n", - "\n", - "This is just a sample paragraph\n", - "\n", - "> With a blockquote\n", - "\n", - " def some_code():\n", - " return 'by indenting'\n", - "\n", - "```\n", - "def some_other_code():\n", - " return 'bewtween_backticks'\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can look at different level of nested unorderd list \n", - "\n", - "- level 1\n", - " - level 2\n", - " - level 2\n", - " - level 2\n", - " - level 3\n", - " - level 3\n", - " - level 4\n", - " - level 5\n", - " - level 6\n", - " - level 2\n", - "\n", - "- level 1\n", - "- level 1\n", - "- level 1" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Ordered list \n", - "\n", - "1. level 1\n", - " 2. level 1\n", - " 3. level 1\n", - " 4. level 1\n", - " 1. level 1\n", - " 2. level 1\n", - " 2. level 1\n", - " 3. level 1\n", - " 4. level 1\n", - " 1. level 1\n", - " 2. level 1\n", - "3. level 1\n", - "4. level 1" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "some Horizontal line\n", - "\n", - "***\n", - "\n", - "---" - ] - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "copy past from Daring Fireball" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "link : \n", - "This is [an example](http://example.com/ \"Title\") inline link.\n", - "\n", - "[This link](http://example.net/) has no title attribute." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "inline Html\n", - "This is a regular paragraph.\n", - "\n", - "\n", - " \n", - " \n", - " \n", - "
Foo
\n", - "\n", - "This is another regular paragraph." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "> This is a blockquote with two paragraphs. Lorem ipsum dolor sit amet,\n", - "> consectetuer adipiscing elit. Aliquam hendrerit mi posuere lectus.\n", - "> Vestibulum enim wisi, viverra nec, fringilla in, laoreet vitae, risus.\n", - "> \n", - "> Donec sit amet nisl. Aliquam semper ipsum sit amet velit. Suspendisse\n", - "> id sem consectetuer libero luctus adipiscing.\n", - "\n", - "---\n", - "\n", - "> This is a blockquote with two paragraphs. Lorem ipsum dolor sit amet,\n", - "consectetuer adipiscing elit. Aliquam hendrerit mi posuere lectus.\n", - "Vestibulum enim wisi, viverra nec, fringilla in, laoreet vitae, risus.\n", - "\n", - "> Donec sit amet nisl. Aliquam semper ipsum sit amet velit. Suspendisse\n", - "id sem consectetuer libero luctus adipiscing." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "> This is the first level of quoting.\n", - ">\n", - "> > This is nested blockquote.\n", - ">\n", - "> Back to the first level." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "> ## This is a header.\n", - "> \n", - "> 1. This is the first list item.\n", - "> 2. This is the second list item.\n", - "> \n", - "> Here's some example code:\n", - "> \n", - "> return shell_exec(\"echo $input | $markdown_script\");" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "1. This is a list item with two paragraphs. Lorem ipsum dolor\n", - " sit amet, consectetuer adipiscing elit. Aliquam hendrerit\n", - " mi posuere lectus.\n", - "\n", - " Vestibulum enim wisi, viverra nec, fringilla in, laoreet\n", - " vitae, risus. Donec sit amet nisl. Aliquam semper ipsum\n", - " sit amet velit.\n", - "\n", - "2. Suspendisse id sem consectetuer libero luctus adipiscing." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "* This is a list item with two paragraphs.\n", - "\n", - " This is the second paragraph in the list item. You're\n", - "only required to indent the first line. Lorem ipsum dolor\n", - "sit amet, consectetuer adipiscing elit.\n", - "\n", - "* Another item in the same list." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "* A list item with a blockquote:\n", - "\n", - " > This is a blockquote\n", - " > inside a list item." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "* A list item with a code block:\n", - "\n", - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "1986. What a great season.\n", - "\n", - "1986\\. What a great season." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "See my [About](/about/) page for details. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "ref link\n", - "This is [an example][id] reference-style link.\n", - "\n", - "[id]: http://example.com/ \"Optional Title Here\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "*single asterisks*\n", - "\n", - "_single underscores_\n", - "\n", - "**double asterisks**\n", - "\n", - "__double underscores__\n", - "\n", - "un*frigging*believable // should render partially as bold\n", - "\n", - "\\*this text is surrounded by literal asterisks\\*\n", - "\n", - "``There is a literal backtick (`) here.``" - ] - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "Other Notebook element" - ] - }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

CSS Playground

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A notebook that contain most of the things that could be displayed, to test CSS, feel free to add things to it, and send modification" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Title first level" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Title second Level" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Title third level" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### h4" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### h5" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "###### h6" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# h1\n", + "## h2\n", + "### h3\n", + "#### h4\n", + "##### h6\n", + "\n", + "This is just a sample paragraph\n", + "\n", + "> With a blockquote\n", + "\n", + " def some_code():\n", + " return 'by indenting'\n", + "\n", + "```\n", + "def some_other_code():\n", + " return 'bewtween_backticks'\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can look at different level of nested unorderd list \n", + "\n", + "- level 1\n", + " - level 2\n", + " - level 2\n", + " - level 2\n", + " - level 3\n", + " - level 3\n", + " - level 4\n", + " - level 5\n", + " - level 6\n", + " - level 2\n", + "\n", + "- level 1\n", + "- level 1\n", + "- level 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ordered list \n", + "\n", + "1. level 1\n", + " 2. level 1\n", + " 3. level 1\n", + " 4. level 1\n", + " 1. level 1\n", + " 2. level 1\n", + " 2. level 1\n", + " 3. level 1\n", + " 4. level 1\n", + " 1. level 1\n", + " 2. level 1\n", + "3. level 1\n", + "4. level 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "some Horizontal line\n", + "\n", + "***\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## copy past from Daring Fireball" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "link : \n", + "This is [an example](http://example.com/ \"Title\") inline link.\n", + "\n", + "[This link](http://example.net/) has no title attribute." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "inline Html\n", + "This is a regular paragraph.\n", + "\n", + "\n", + " \n", + " \n", + " \n", + "
Foo
\n", + "\n", + "This is another regular paragraph." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> This is a blockquote with two paragraphs. Lorem ipsum dolor sit amet,\n", + "> consectetuer adipiscing elit. Aliquam hendrerit mi posuere lectus.\n", + "> Vestibulum enim wisi, viverra nec, fringilla in, laoreet vitae, risus.\n", + "> \n", + "> Donec sit amet nisl. Aliquam semper ipsum sit amet velit. Suspendisse\n", + "> id sem consectetuer libero luctus adipiscing.\n", + "\n", + "---\n", + "\n", + "> This is a blockquote with two paragraphs. Lorem ipsum dolor sit amet,\n", + "consectetuer adipiscing elit. Aliquam hendrerit mi posuere lectus.\n", + "Vestibulum enim wisi, viverra nec, fringilla in, laoreet vitae, risus.\n", + "\n", + "> Donec sit amet nisl. Aliquam semper ipsum sit amet velit. Suspendisse\n", + "id sem consectetuer libero luctus adipiscing." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> This is the first level of quoting.\n", + ">\n", + "> > This is nested blockquote.\n", + ">\n", + "> Back to the first level." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> ## This is a header.\n", + "> \n", + "> 1. This is the first list item.\n", + "> 2. This is the second list item.\n", + "> \n", + "> Here's some example code:\n", + "> \n", + "> return shell_exec(\"echo $input | $markdown_script\");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1. This is a list item with two paragraphs. Lorem ipsum dolor\n", + " sit amet, consectetuer adipiscing elit. Aliquam hendrerit\n", + " mi posuere lectus.\n", + "\n", + " Vestibulum enim wisi, viverra nec, fringilla in, laoreet\n", + " vitae, risus. Donec sit amet nisl. Aliquam semper ipsum\n", + " sit amet velit.\n", + "\n", + "2. Suspendisse id sem consectetuer libero luctus adipiscing." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* This is a list item with two paragraphs.\n", + "\n", + " This is the second paragraph in the list item. You're\n", + "only required to indent the first line. Lorem ipsum dolor\n", + "sit amet, consectetuer adipiscing elit.\n", + "\n", + "* Another item in the same list." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* A list item with a blockquote:\n", + "\n", + " > This is a blockquote\n", + " > inside a list item." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* A list item with a code block:\n", + "\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "1986. What a great season.\n", + "\n", + "1986\\. What a great season." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "See my [About](/about/) page for details. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ref link\n", + "This is [an example][id] reference-style link.\n", + "\n", + "[id]: http://example.com/ \"Optional Title Here\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "*single asterisks*\n", + "\n", + "_single underscores_\n", + "\n", + "**double asterisks**\n", + "\n", + "__double underscores__\n", + "\n", + "un*frigging*believable // should render partially as bold\n", + "\n", + "\\*this text is surrounded by literal asterisks\\*\n", + "\n", + "``There is a literal backtick (`) here.``" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Other Notebook element" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A small tooltip\n", + "\n", + "
CloseExpandOpen in PagerClose
And some text inside
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "
\n", + "
\n", + " \n", + " Close\n", + " \n", + " \n", + " Expand\n", + " \n", + " \n", + " Open in Pager\n", + " \n", + " Close\n", + " \n", + "
\n", + "
\n", + "
\n", + "
This one should be big
\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ { - "cell_type": "markdown", + "data": { + "image/png": [ + "iVBORw0KGgoAAAANSUhEUgAABDEAAAJXCAYAAACKd8/wAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\n", + "AAALEgAACxIB0t1+/AAAIABJREFUeJzsvXm0ZUV1Bv5VnemO773ufj23gB0QBAFbUBORiEaFxgmX\n", + "MvgDASE/ZZmAicbg0iCYYFDR5S+QmCUosQFBooBGHICYgKDBGRUkoARkapqe3njvmarq90fVrqpz\n", + "3+vu180TGjjfWrfv6zuec+45u/b+9rf3ZkophRo1atSoUaNGjRo1atSoUaNGjd0c/OnegBo1atSo\n", + "UaNGjRo1atSoUaNGjbmgJjFq1KhRo0aNGjVq1KhRo0aNGs8I1CRGjRo1atSoUaNGjRo1atSoUeMZ\n", + "gZrEqFGjRo0aNWrUqFGjRo0aNWo8I1CTGDVq1KhRo0aNGjVq1KhRo0aNZwRqEqNGjRo1atSoUaNG\n", + "jRo1atSo8YzAM5LEOPXUU3HOOef8Qb/jiCOOwBe/+MV5/9wHH3wQnHNIKef0+ltuuQXPe97z5n07\n", + "atSo8eRR26IaNWrsDqhtUY0aNXYH1LaoxlOFZySJwRgDY2yn3lMUBd7+9rfj+c9/PjjnuPXWW+f9\n", + "O55JuOqqq7Dnnnui0+ngrW99K7Zu3brN17761a/GkiVLMDQ0hBe+8IW49NJLK89//OMfx5577onh\n", + 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CloseExpandOpen in PagerClose
And some text inside
" - ] - }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "# a code cell \n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib.colors import LightSource\n", + "\n", + "# example showing how to make shaded relief plots\n", + "# like Mathematica\n", + "# (http://reference.wolfram.com/mathematica/ref/ReliefPlot.html)\n", + "# or Generic Mapping Tools\n", + "# (http://gmt.soest.hawaii.edu/gmt/doc/gmt/html/GMT_Docs/node145.html)\n", + "\n", + "# test data\n", + "d= 1\n", + "def maltc(ax, lambd=1, n=1):\n", + " I0=1\n", + " I= lambda theta,d : I0*(sin(2*theta)*sin(pi*n*d/lambd))**2\n", + " X,Y=np.mgrid[-5:5:0.05,-5:5:0.05]\n", + " Z=np.sqrt(X**2+Y**2)+np.sin(X**2+Y**2)\n", + " \n", + " r= np.sqrt(X**2+Y**2)\n", + " theta = np.angle(X+1.0j*Y)\n", + " \n", + " Iv= np.vectorize(I)\n", + " Z = Iv(r,theta)\n", + " \n", + " # create light source object.\n", + " #ls = LightSource(azdeg=0,altdeg=65)\n", + " # shade data, creating an rgb array.\n", + " #rgb = ls.shade(Z,plt.cm.copper)\n", + " # plot un-shaded and shaded images.\n", + " #plt.figure(figsize=(12,5))\n", + " #plt.subplot(121)\n", + " ax.imshow(Z,cmap=plt.cm.copper)\n", + " ax.set_title('d=%d lambda=%f'%(d,lambd))\n", + " \n", + "fig, (axes) = plt.subplots(3,4)\n", + "fig.set_figheight(10)\n", + "fig.set_figwidth(20)\n", + "\n", + "flatten = [item for sublist in axes for item in sublist]\n", + "\n", + "for ax,l in zip(flatten,range(len(flatten))):\n", + " maltc(ax,lambd=(l+1)*pi/8.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "\n", - "
\n", - "
\n", - " \n", - " Close\n", - " \n", - " \n", - " Expand\n", - " \n", - " \n", - " Open in Pager\n", - " \n", - " Close\n", - " \n", - "
\n", - "
\n", - "
\n", - "
This one should be big
\n", - "
" + "name": "stdout", + "output_type": "stream", + "text": [ + "stdout\n" ] }, { - "cell_type": "code", - "collapsed": false, - "input": [ - "\n", - "# a code cell \n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib.colors import LightSource\n", - "\n", - "# example showing how to make shaded relief plots\n", - "# like Mathematica\n", - "# (http://reference.wolfram.com/mathematica/ref/ReliefPlot.html)\n", - "# or Generic Mapping Tools\n", - "# (http://gmt.soest.hawaii.edu/gmt/doc/gmt/html/GMT_Docs/node145.html)\n", - "\n", - "# test data\n", - "d= 1\n", - "def maltc(ax, lambd=1, n=1):\n", - " I0=1\n", - " I= lambda theta,d : I0*(sin(2*theta)*sin(pi*n*d/lambd))**2\n", - " X,Y=np.mgrid[-5:5:0.05,-5:5:0.05]\n", - " Z=np.sqrt(X**2+Y**2)+np.sin(X**2+Y**2)\n", - " \n", - " r= np.sqrt(X**2+Y**2)\n", - " theta = np.angle(X+1.0j*Y)\n", - " \n", - " Iv= np.vectorize(I)\n", - " Z = Iv(r,theta)\n", - " \n", - " # create light source object.\n", - " #ls = LightSource(azdeg=0,altdeg=65)\n", - " # shade data, creating an rgb array.\n", - " #rgb = ls.shade(Z,plt.cm.copper)\n", - " # plot un-shaded and shaded images.\n", - " #plt.figure(figsize=(12,5))\n", - " #plt.subplot(121)\n", - " ax.imshow(Z,cmap=plt.cm.copper)\n", - " ax.set_title('d=%d lambda=%f'%(d,lambd))\n", - " \n", - "fig, (axes) = plt.subplots(3,4)\n", - "fig.set_figheight(10)\n", - "fig.set_figwidth(20)\n", - "\n", - "flatten = [item for sublist in axes for item in sublist]\n", - "\n", - "for ax,l in zip(flatten,range(len(flatten))):\n", - " maltc(ax,lambd=(l+1)*pi/8.0)" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "display_data", - "png": 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aCEylBbb2NAnUMo6SDni884LrC78PYYgMbVSUUJBSQgQKJZPWacHAeSSsIaoJ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DxNmCw5aF8sWnz34Qr/67MtfuWTHf7D4w0+3S2w7CqMs8dXNwOsD3h9mLKOqEAvK0N5wJKt\nTIV61lufGa8gTzibSrOJJt08LlATNCLrsUlDS4X7pq/xZNPjFx6u8GjdwWiN/Tjj0brDuq2zOdUl\nCMiYPZ5fD4k+eX2a8fymx65vKFear9Pr44SX+xGvjxMOHM8qMYbSNCxa2mi2fYM160zPqGaMtp5Y\ns3XgifcwZ9MvF86ptx8yQJDNdvYew3x/WH/sa8tMjB0X25ue5QNcRA9Ws8syUo73wClI+4ESQOhw\nmLFbWrSjha4NoeGVyTemImPeRmQEHEO4aCosGmrs28pgrNjoVxyxPTXKAr7N7py1JFK7maOIk3SB\nnzcBMBZ1njRu2eth3dboC/mFAJTy3B24GT9MDiferyemHIrc666IwBK8EHA5SyeqZApFhlAEOCfD\nr5ALlP1ocS1mYEzvBFyS3cmfobg2Q6XPQAwxA5sY5JmY0SXDGWNUBpdqg0VjsGhq9C0BLm1Nrz+Z\nZEcuDkjHAowOnj1Vrvle2A8UTZ0nHLRnA1IcaLRN1pdue2qg7tfHvSS2+d9yDi5NsTyTYB14bpLz\nihy7pwKb9N0CMvLEVc5dtiAtJphaSeqOMI0M1gxmLNsKpjbJG8NZj3FusFnMySBO6rae2Rjik3Fd\naTSjJqPimfcgRzp6SUd623WTayDy4oop0h2nj6y5DrlYdni4avFk0+PJpsfjdY8n6w4P1x0erFpi\nqDYVjKSihQhrHeqJgJnJ+Rwrq8Q0WWV2TTGtDvHNpJASwJAarvT+kM8KUSIh6TWU78FPeu/Ifni/\n7hcA9HVFNU8Uab2G9cRcogY1G+aHBD6UnlohAbJABjLEILI2GkoZ8hLjhDHIvhByFHNiY7MsvayL\nhGF5M1RYtjOWxxrrbkpS0CUbTnaNoaGSmK2T3wAQKyBEGB+wZTCCAiECeTXwtdAM+kriilEOlVZc\nCwUm38b37kOyhP0pe2Ue8NCgSXyFdmzk+Xjd4emGWBdPNxSj+mhFJp56wUlpDQMYGoAHM0Qd4ugw\ncH16eZzw+jDh1ZE8066GGTcDsYmFtSuDlspQ9PuyzelMYnC8W7bYLVtsxeeRQakYI7RjTwzev2Rv\nOgO6xGKgqB3lmpAPBskTZf9/3/p3ATFKCjYZicSEAL1vyUafwIvaoG9qrLoquUdvE7JP7thGyyET\ncJosrgaL7iiHqeSoc9RpJMo2OdNSrOHkPK6GGY0xiIgYZo/r04TXxwmvDiOuTzNmH1Bpjd2ixXce\nLPErz7b437/zAL/62QP8hydrPFn3qCqNq+OEEIEX+5FjE/MEJka6eSjilW6QujL02kXiMpLeOgTP\nTQptDDJh7dk8BwDLPhzUMOM4nd9ESgGtMdj2DZ5senzv0QrLpsbkPJ6se6y7Jr0+mRlcn2b62fsh\nGem9Po7Y9A3fbJTzvh9mMhk8EYgxWZ9iDGujct7xkuKCdosW2wU1jmJ86pgxc2Ca2E3RMB4qk41o\nXEjSkXfdQdRLxpTnPNnbM4779TGubdfg0NtEkdsUe0fXGDSzxmhVekZTckjRuF7xgbA9Tli2NZYy\ntW+4NBSvDJQU5hxX1bK0o60oyWfW5GAvzTk4TlmYBcbmpjoEnGd9C8INZl1Vig9GAi8uWON9sWgT\nYNM3FSqj0vcfrGdmwYxr/h33pxk3rDsdrMI4e1gEWOAMTRddY6XZ8I+lK8s2G2VuxfiPGxuZzADZ\nb0c8g1r+f1LQy7EnAIYLAdGW5qsaxngYJbKyLBOcfWb+Ib1OobmytK2m973l90e8OhLnVHx0QgAm\nBwwzDjzZkI/rQTxJbEp7kqmU5si5nlNQ1l0+s+7Xx73EJFfOqm/SlJbMCzHPlmI8MTZvgxhgkEJF\nus35nk+vSf5/UZCSZ1c4866Sn2+0AITEAGv6hlJ9DLnVVyGgnR16YWG0FfqWpW6VQcODnKbSqDka\nseIo1mFWmFWA8iS1TQyWO66DULVFYpz8O9pcnD/gWuTxhhqFp1sCMh6tOzxcdVhxbKESk0DafKAn\njRAjRltENyKzLpLHWsgGhT4I8HJexEujJ/GCWiOB1efvUZb1eGbcBtCHSE1+kvsmnv/jfn3Eq28q\nPj+JWSGxppQAqJNPhTDoRRpQxh1LTKdIoHQxbO2qiqPRIyb2l6F7V5jS8rM4+pOTxJIBOQ8mjpND\nW8/ojyTBWLQETC6Y5dnVBk9qA200UtFUGdmgSCLa1qh9wM7lGur26wcyGKygoBiEUJYSNLUn6wPP\nlIx3AaoCYEgwgfjxiAeGePLInvRIGGHrHo/WPR6uWmwXDaWQtOyBYVir4EGy5skBg4U9Tbg8Tni1\nH/FiP+LlYcSrw4jXh8zEOLF3l+NEEc21mySREKDS4mLZ4MGqw4Nlw/VjlgkqkD9bRMTscmockQSy\ntwm9rzGdFRn8RpKR0J5v+Jq8H6L4d/HEOM0ek1CUvT+bqL9rpQdBqxSzKdPF3aLBgyUbMK1a7IoC\nXXSYEk+4Pk5oTXZSlQdGNFekPfdQakKIZLDXnWbW/MScBsBUHMvxp9u+xifbBX7pyQb/8bML/B/f\nfYhf/c4Fnj1aoelbIFDCysvDSN9LZBPceGhFDcduQRqo3YLBgQgcJ3LYB0ZO4CBNt9FAWxusO7rB\ndn2dNqBh9rg8jjS/9BGDddyIcbMDAoPWzMioVy0iFLbrLpl9Oj6EJaJxP8zk6XEYU4LCqqVmQzSi\ng3WsQafoHhtoKlxpha6mB/Vi2eDxmgqGx+sOF8s2UU6hcjziPiULjHh9ZInQacLNKIaeDtYxvfx9\nQIYgxgggkxX3js++Xx/Davoa26nBbmix7SemPjeJ2nyoDCrjEYJnE11OA5moyb86zbg6Esq94WK8\nrjQaBao2tSLpQSGBSmZXlU7Ncsuoc1Np1E6TBCzmaDEgcPqOglEBKoEYJZWTjJKB7IHRVdQsb/oa\nD1YtHgpVetXhYtVh25PxXmPEFyMmkObqSM35q8OE17XhRkLBjIp4zXDUeKnCnElJTCEBGHIob3s6\nBB/K/syo/rIjTxBKgiEm3GFyuD5OLGnTKcYsRiBA3MGRNKkukjeGaGq1C1SvRElQYYpqwRwpNZ8t\nT40FSGqZEi858DJJVS4As+NoVQ+MFgNPOOiD7odE05x4/+O9SYGirTt2+V6mCUeD7aL9md3z9+vb\nuaQ5BX7yRlRaXpXACtKkS0OsC3kDeUnJV5FELIQIrwK0jlBePMlyYS7sJpfiELnw54mpZTM+YYqC\nKcKV0VRstxXF/7ExrnI12rZGndJJCFSsjCQo6RSlnsy8FUUfKkXn94yAAA/FwMttYECfARh5urju\nybfjwaol6Qjrzp9tF3i6ocjCh6sO3bKFEgAmpRJFYHJQIVAcd1G0u6KZk2Qiy7Hcct18Ue+WAEbF\nQEilNHSRoAAGcOUeETaMYsBJMcokkpD31UJvW/cYxv0CgL4xZ6ClDdmjrnYe1iiKCeWNShiPKRSB\n73lJF5EJP7HnDZqaBjkA0PnAccUM/oWYBzM2/1zLfeJkCVwQGe2BpbidMFyrzOJqapLxPmSmBwC6\nvyW6UyuKYG0M6r7G1pEp6Mxx8NYTO0PqiJRfrIohqAIsJCTg7UDGbQCj4oRF8pwgdvqqoz1pt2jS\nwOlhYSy8W9IwqhL2RcXxsYE3AKlRTjPiYcTrw4gXNwOe7wd8dTOwZ+GIq+OI62EqahTaj7RSiTVL\nxIA6vxZ+DQ+WHXZLqpO7OqsFJraH0MpDgf0Lb50TCcwIedgGAEokx4XkSNQV71s/exDjZNl9NqTC\nskzbeNsSPWOlFZraUHHeVRlFX1Nx/pTR8wfLNpmOGEUo0XEmGciirc5BBH5IPDMexNUeYP2V9Ux/\nUulzxLDShwitgHVX4/Gmxy88WuF/ebbF//bJBf7jpzt85+kW5mJJiN9o0Rwn0lJyzNhxcpisg49E\nq1p1FR5vOnznYonH6x6LpoKP5MFRVwNcCDjNHiftAM4+byuD3aLBs02PJ5sO666BUsBhtFjyZjQ6\noYEzXZy189YHKNA1xbKDair0iwa/qHVipQwzmehYF+B5Ujq7gJthpsnp5NImJNd0nD0mdhmO3Mu1\nNT2o20WDB4sWT9YdPmF33ccbMhjt2ZRPfk9hvLzoSCcr6GXKeJ4AASPeB2RIEUbTpRzve78+3qW6\nGqvUSOb403WSlFRojEuFuRhpnhhguz7NuDyN2OxzXnZtNB4AqHxk2mIErCczKC/xVbm4FxmYGF7W\nRmE2CiqqMyAjMpChtYZiO5c0Gb1VFAsTYtEQ0LtdEF06TRp5n7xYtlh1dZKUuBAxWkoNuDzOeLUf\nSJbHTuLJayIQ7ZImjJkhoRRRLsWDY93VeLBs8XBFTYJMNx+tunS9W5btuRgx8nV93dXo6oppprlx\nKmmq0ZLZF1BQ8WP2BwLKgh9nh2Y20io0mAxeVFoKKo5+CwHeBWjrQDxTBTiPeSBw9dVhxKsDsfIu\njzLhIJ3pbLPbd0mnXTYVmWQxC+NeTnK//q08MG4DGMZkzwpdgAFaJCbFz/cR8EHB+QjF7gj2VmFO\nDDEx3SND8Ml5jFwTjfzfk/NZ+4xIVGcjBrlSfAegNtC1xsrI6xLmFdKf+UXKdI8b+uBoLwgKVmUQ\nSJZWCpWi57wxOk1r19wsSHLck4KBQSBGj4ebDu2qA5YN0NT0upUSShzg6XeIyMOwycmATmpEh9GG\nZJonw6CSNZKAFm5qJP5a9qH0FkVw5DeSxlyrCK2YsRcCfIJovyGQcb8+6tXXVfLVc5IYUhtmRhhY\nF+FUPDP49IH8rGZfflBj6yP1V0rl2qStDIyhnyHSeU0ahOTlJ2CG5Rh78lSwySdjtI5ZVvPZOS5h\nASn5DMAOgKJJ5hmQCgAwGqrKktdNV5NsjZ9bSTv0XPfkcIk8gA8xQkeFcMc+JIvqPs2+PDpFl4o/\n1pr9PHbszyMpSVuONF2yXxBKj67ANUlgAGOwiIcRL29GfHU94MubAc+vTnh+PeDlfsCr/YjXJ5GS\nuNTzKsXplbVhCQknNK06POIB2MMVASukFKg5Zhqc8hkxWpVMWn0JfjGTRsAh8iCRawJUig3fk4ww\np1W9b/3MQYzjZImGGN6vZby9VOHg2jUGy7bGjieMTzY9Ptku8OlugSdbKpR3fYtFY2CMxuw9DoPD\n5lijrUh/PXuKJ5TDxjqfqFMhEJAhTbnR2btCHiofI4wC+rbCxbLFJ7sFvsdmnr/0ZI1nj9YEYKx4\nyjZbOBdwmFyWRkwWs6Nioa8rPFx1+Gy3xC8+3uCTXY9lU8P6gBf7EYgETFweJy4+IrRW6GqSnzzb\n9vjuwzUeLFsYrbAfZyxaMuwcJvKWOE1k4LIfLW5OFMd4nB2Cp+9F+iqDOgLfm12axl4PM9Gj+ZqI\nhuo0ERAixi5ATO+vLTRWNft8rFrSxz7ghubT3QKfXpC56INli2VXwWiiqx0nh6vThPV+RMfUboVc\nRLkkj6HNTSn11s2jXOU043595KutUEtsVN9g12dJyaqr0Q8zGW6y6VH2bPAJxHh9nLBqKS9bpBER\nwMYHmjYoJPBvch425KSK0jui4g9jNGodEDRrnqV5CJENp3M0sLAEyukjeW+YBBqSlKRJ9MSnGzGG\n6vFw1WHD7C0CezNj7VU/MV3QEPUTHDXrMs1z1gGaBwFJ6qcJjFm0FbPkWjxed3i2I2MqoWo/YPZV\nW2cA5cRxt31dcVpJprOKW7lldD8wsCNTX2pqAuvIY3GNzs8ZrWQiVDYOKiWk6AIAESf00+SwAHlo\nhABM1uH6NOPlfqSPw4DXB/IBuh5m9gIiU88QY9oD2zo3UaWUZHMvJ/no1zcFMFLTfwvAqFQx4ec/\nheFUNsmJyh00HD/XWimeEYQkeQ2RE4S0QsUpHKeafIIOE6WJHDpO6pklKSCg8oEKbSDr0yUtgJuX\nPgIPA1GQxVDZcTMjmvtSnuFCgIsBPmio+KZRtzBOjKECWaRtAuwKbfthYeb5aN3hwbpDu2yBRQN0\nzMIQOnohKYs+YLYeJzYOPk4Ox9ElORmZCbu0F0js/DmNWqE2JsVNS1qTxF9nQLaofXyEVwpWBajU\nDugzIONDaqH7db/uWou2TqECvqjnZxcwVwZzRT4Z0qzS1J2CE4R1NCVPCxqAhkAAnDDqZWiglEJb\nhXS/AyQRKxkglr93KV0TI9Fxdjjw3pY+NIO33JdEECF26wNqF4DWZ1mJbGoAFJtJdmy8vpxrrDsO\nFxBPMEceg2JSKUqCEBRCVNCR6rS3scJkGC8myKXZ+7LwdZR492VTY8FD3KYyUKagmTqf5crOI44O\n9jTh9X7EVzfk2fjF1QlfXJN34/ObkS0QROrvstRfEyN1xTK7i2VTEASytE5Y831dcT0UMSFgdplJ\nk6NyC28TZmqIp2PGjxSqSqE1pK7o2IuDTO+/hSDGyKjP1z2wRY9ktM6U3MZg1ZM+59GqJRR9t8Bn\nF0s8XnfYLFvUbUXeFz5gGGb0jaHpgiUGwZEPXaHVCCMj+1QEOAVoTQeFTD2RqDca667BwyUDKTsC\nUp5uFuglt9fopFO6Hma8PlLhe8nGl9ZTfFEy2ny0wi8/2eCzB0ssWzID7RqD42zx1X6kqSmTmYwi\nicZuQT//ew9XeLbt0RiNm9GiqyvMzuN6pOZg4gfxwOkrLw8jLg8jrocZF7Onh6EyQF9jue7wjGN9\nnjMNaT9abuiQMoWDDbAqEAjC10imn6mp4o1h3TWce0wPRwIydktcrDt0XQWlNUIImCeHzYEkJhqE\n7knMpcTgTtZgshRpq0IelLxvJVbG/fq4V1NBtzVT+5tkNitAxoKNoUarEw2YTGepYL0eZiyPdPD0\nLWn5NDffs/NYNMQm8Ex9HGaS0TkGSoGYGg+jhC6t02HHZyEgfzJogVuHpCxVSFV6NqsUhH/LtEAy\ni+rxbLPAo02HZd+gaWkyEWOEnz22g7BKqMmRaGVp6CVSkDTgeSWHaT6MVi3FOSegebfAJzuadF6s\nWnR9A8PFRPQR68li0VTkXg4CTAbrU4MwzOIzYWgykqYhfI0iaXTTa4pnf3AxoVKUV6KpKw3F+5cU\nbmIuPMwOFQOr8tksyjoAACAASURBVF4eZ4er04wXnMT04mYkwywxruYJh+XDWkxdJZnlNoBxn05y\nv/4tjyMCR6k+kIjA8waZPko2BjG+AtN/Od7ZcYPsASCkpDMBMibrUWmHpuL45ppM9lZDjesTFeOU\nhmTRNhV0UwF1AEwAtJGijlgOoQJ8wMIF7FzLZrwEkgwctzxZj4k13JMlcNlqDasDtFfwKm+KZJKJ\nxEIpTZUFyNgsGmzS1LPBbkl/dn2dDfNqBjCEti3JRLOHYwPimxMB2tcn8gO74cSqw0hJVqP1yf8t\nFq+vBDBakdOI/wf78cheFhLIpGA0vUdwuhADAREKkX1C1FvOiPt1v963+sZAFBjJo8LR8z6585AB\n6ec8yzZnT58jqWDyNTSBp4ABDTHYzX5cjXhQqZzI6EKWZllOKxE/jsgsR/HRKpPQpJbK6Y7yO3hs\nrUfXN9BNwQgj8yyAmfWl/CzJVJgZsODfpy0kdNZrGB1hYkTwioHE8yXm5FJzJEPPipv3JrMPepbX\n9WwunmotBcRAUj/YAsDwAX5yGMYZl4cJL/YDvrwe8MXVCZ9fHvHF1YmkJPsRlydKjRykPsG5kaek\nokidKACGgBjbBfs1GqrbxEtSYu19kCEXvf+ZmZcldXmIV+yBBQMjAzrfQhDjtiOpaItK/yLR9ZUS\nE/o7ldAsaYz7RJcmRF0oyw+2PaplSxpMpWGcQ9UYjgINOE4WV8OMzZHcbBdthX6SZiWkwrikCsnr\nEMJeZYgFsZafL9QffpNRabrBZjKAc/sRX1wTMvb8ZsDr44TTTFKIrjZ4sGzx2cUS33+0wS8/3eK7\nD1dYNAb7wSKCzEBXrBOX6yXGnquuwqN1j88ulvjegyX6tsJhtGiMxjA7vD6MeLUfccMpI4fJ4tVx\nxPMbSVgZsNn0MG1Fh3cEUGnSaC3ICFBoTYeR2CN+imywd/c1oteH5Abe16UjPz8oa6K4P9z26Ncd\nVF8D2sCEgJpfP4BzCv8woxtMSmK5Pa2QJegn7ri/xDX3fn3kqzJAU6FhNoaYA5dsjJvBYqgoEccz\njXFiZ+z9aHB1JHlAV1MslFaMTluPRUvJGzGy34NEBQpgyk1uQum14iFlvq9VwbRIt+wd964g/FUy\nDyXGWs+RoYTu8wRy2eBi2WCzbGFWLdGlKw0VI6rZY9lUMPK62Z/mwMkbV41JMa/iV3H+Osq8c2rY\nd4sWDwvg8um2R73qgJ6NqRSZZLVNZmUMljLN18NMjZAc7rPDUGlMTqMWpkox3QTeDVCKNFHiqLVW\nyWMkgiSElg9g8uXRCBEY5mw+epgsgxg08XjJ+tMzsyxXGhozC6PJenwxOKU4uHsmxv365ksVzAol\noKhWaT8QyrUAGuKTIWBpSE2DRqU9jPbUzFj5CRnIyECfQzUq1MZmPXNNtRntP/nv1kZDUQY8LY6K\nToJxo6H4axZNjVVrseoqrKaamA28n7WzS3uQ0eSPdef1QPbESHsiNwdSJK/aHHUshoBJ8iKUbbo4\nNPlkQ994mnFznPH6MOH1cUwfIinLBr+y32dpmYJMY02ilJ978phk8pmHxZzc4D0xMBSIheEiAksP\ntVIIKht83q/79ZMsYUJC8VAylNJ7GiKQB4JOjCmRmcrUfWTgcbTcxJY1DyIbj2u0nE6SpJzSrEdi\nnYrPhtgPyM8TRji1WAFH5RILrdwHhRlgPafLWY/t7Ni/jCQt9HkEcjh+fQoEAMu+IUBjI8/oLfmX\n1QrK0zW7ixWe2BjcuFc6+2IIKyN9b5G2Gl3sAewvYT1qRCi2PHA+wNrMDH61H/HVfsCXzMD44uqE\nL68GfLUf8eo44nqwxKDn1D2jkbyCZND1iFNRnmwooemJeBcuWqz7hmT/WiW/pEnlZBl5/wWEHmef\nDM5tAr7omuRa8TxeVnyLlu37hzs/cxBDNnClWB6iMoVIVhC9TLjtlZE1z1pJvKrJrAxG1teLBtWi\nBQoQA54YGUsXsB0tU3WqFOnV1VlDZXRhWoO7p/aaC4MUzddSgd1WlIYSAELKhpmAjMOIH7864p9f\nHPCvrw746mbA1YmYEVoprFry1PjswRLff7TCLz0lJkZdGdwcJxxnh4tFk91g+ZJpRQjmsiH6z7Nt\nj+88XGHR1ZhmB6MpLvbL6xN+fH3Cy8PAHhcOl8cJz69P+NdXB3y62+Ni0eCZVix/UYAlPNEUBXgv\nvydPGgUIvOsaUbOgUqyZFDhlFO6GAY1+0XDecU3FTAhApVHHiI31WA9ktijRaxnAEPbFWzYMLnCE\nJVLeY8K4uV8f8apoClgV2dzZF4PpfG2F42wwFiiyLdJzOm7WJZJZIgQn57Fq65QWZH3EabYcL01+\nCTP7zMhhABCoK/e1VkB4x8uXlRgGfEAaQ1GjjTFncVUlyr3oapiuJrp0V7N/B4DaQRmFLgTsrMN+\nbHDV8/PHDUltRN4lbvxMx9RF7nmlE7IuLtcEXjaol7w/d3WmdVoPKIXaeSwnaiZkX+24yG84nq02\nZLiqXWDGSvbleOd1kgJHAHFpfiJNOBwXaaPzOM0e7Ujd2+xCihGbvMdhYBBjP+AFTziylISKN4ly\nzRJIusfWDJit+3y/LT5g4nC/7te7VqoJoIoEEpWi6OUMlka55lSAZGALsnxxrGdvjEPtssSKQFWH\nGdnszvrAzCYPM1p+7oUqbdIeJPRuAFiDtek+FD4ToP9mQEP8Y/LrNWirihNLyuaBfSOk4b/lzyPN\njDCvaiMRfuZsCtpyTSHxzOliysQTzFK1Dhgt4nHG1X7Ai2SYN+KrG2LYijfOzYllZdzEldHO4sJf\n7stdQ15vLYPhhpkyQK5XrCNzeEXUmDQBN5GADBUiA9/APQfjfv2kq28qVI7P9igyepJXTq4mlgX7\nHJyxMZg1Mc4eY01nqMjYc0R7loAaRT4MptKoIzWzpawkMDCSpWTZGyvwHjQ7nwZLFB9demIhAR/C\n4h5mi+PUYd1V6BuyF5CkFOvJZ2O22QgckZ4pYXgk02EGL7LHUP5427OXBlOJdUtASZK1apWMjBXv\ni4H35Ml5VJY8gCrLkfQxpgEv+ZhNeMFSkufXA768JgbGV7wvXQ8zTpPFxGwW6R8lEfOCB02P1xTl\n+mTb48mWAIyHKwqbWPCACwAcM2xEimidZ4uGzNgVX8WRQx7KdDhjMhtlwRKeVZdr79W3EcQwxZue\n3LJFa5hMi1jzh3CmCY8hU+pKPwOtwEW7RmcManabRWOygYsF0BhoLoLFTK8RPbTRrImmD12Y1txe\n0pwLTdEUE0mKBiW9dFsZ1KOFcx4vrgf84/Nr/OjlHp9fHvHiZsB+nBEi0DUa2wVFnX62W5Ik5MEK\n7cUC0Ao7rbC9GbBo6mSgqVRG/IwCU4Fq7JYNVusOWLboncd3IvByP+BfLo948uqALy5PuBlIwnI9\nzHh+PeBfLw948rLHuq+hAFyMlnxEJoebwTJYQePiRHnXObbtbdn25XS5KiisdSqouNCpNFTNhl91\nRdCgoCNsKtgWEWsCRwitNRll3WaAcOFU6UzFEh6+5w3qMN0nlHzUS2lq3psKbZvZCuuuwbqvsWZU\nuB8rYmM4j+DZ8NdldlB7nHkvYQNgYWu0Lh2S8neHyeLAxrri6Jzka/mFJffrD5JIqQwMUwJBfv4U\nH4i6eG7FXIo553QNxHkfAHwgk99aQATN6SkCYGSg5fYQVMCBmimZBGZkpL2rK6JpN4bzzSVqJdJr\nEeMrk/ebskAQqY1WwvImD4yCSf62S5RkidKjCPjqQkypAqNl5slkYTQntswuvYcjs3Aouowkea95\n+noQgKpgYRhNssNFc56MsOkkzrdG/QGH9f36eNbdvAJab7vHhdElXy+MI6Ev1wUboa1z414Zmfir\nQtseMVmNZvZ8fro8bIrnQMbsyVBOg+UrSpMkLj2z+XWTW33A2nlUfQMlDvsAgwQesCGdz5DvqXNM\nqtEFA+PWz7jrQiYwR/Y+w3UB1wbaCJMzx8dq65HMfiyDLM4jzg72NOPqQM3Cl9cnmnheHUlzfp0B\nzZvBkpRkdklGUgIYBNIS44TAZaKUS62T6PCx8AfQAdr6xH71IcJrRR/+64XG/yT32P36OFbPYKHh\n6FNiXUX2NxB5gOPoU0pT88jAZvYbtDjNdWpmSRKWpSUAxY6jIpZ8VUWsC+mEpPAQGyQkVgj9HRnd\ngmXmPlBypCzxvRMmhzADjjPJvDY9nb1dQ32g7H+zpx5ussRWsPwzkwyMKzMZiEg/Vu5B6o6Hq/w7\nXXytJBDJICrGW8+88xhtriHFfzAltMyOEt1OE16zwfjzGzLxFA+MVwdi4R9Hi5H9SRTyAFw80wi8\nkJQmkhw/Wfd4vO6xWzTouxpagOcQodI1jvw6CcA6zeyHxEBGaWxc+gFJvH0JYKxY6kd/fgvlJH1t\nzqKzKp21yIhZizyrgNmT1i/RFwuvCtFp+ZQawOYyCfEoK9qIJA4MWSYSIjE+3vj0r7HSzcbo436w\neHWY0DVHQs60wml2+PL6hH98foN/enGDz69OeH2aMFmiBC6aGhd8Az3bLvB0u8Bi2wPrnl6dJW19\nU+sMmBRL4mkI1a+BvqEpZ4hY2YBnW0oAecQ34svDCOspOvbVYcTnr4+44GQQHwKenPrkpfFiTzTp\nw0QmMDkON37wgZmO1lgYEcbyfYC4bXK3Fou3jf49FA+LvPeuaP5kcwMKrWmVi7Yc1ZipY+4exLhf\nCtQJVxptk+VO6z5PzClu1eI4GYzGwwVK3LGBnqHaODT1jLrKjB8xAF21jjxdlCD9IQEfB55OlMlB\n3jN4GiPOIY33N+iyyr2MnPtz3JX1mZoZAhvt0YOY3TnlOzIVRHNjosvGQWcg9Y3XwmCK4s+hhkNn\nenSJfsjEUJ5/fh2izZcCxBf7zhtb+9ddxRER0pnCxYIj/f1hytOZafaoUhZ6EUF7Yn8jmbyyUfNU\nsDCEJttWzIARgKwTuRKxMOpav+9V36+PYMnjdFcRDCA1wsDdt36MEfF2faCyN4bIvNo6N8wyyJGY\nY6lnJmvQ1rdkGwwgwhZARoiYEaCsy+jJrddUPmOT83gwO+yWFm1Tw9Qm+9H4AD87nGbPAG9OsEts\nLyU/5uu07HJ9y1hZqd+QdNwTM7CWykKHQNIXUL3gZ4+BZWSvDjTt/Op6xBfXR3xZTD1flbIyji8U\n939JZpAUBKJO11ixkZ0wzmTwAmRPgtkHaE1NmtRCJihor+64FrH45+1rkO+Lt617KcrHvbraICBS\nHDNU6r+sF2lIYJPLwGaNEYGZ21L7UDNLgP9xsjiw2e1pdpz8IdISrgnYY8FUGitdMPSZJVmyp72A\nGuk+J8BBgAw5333Mz8/EZ7v4IG4XTZKQ0TNHu4qXhpyHVEkK4UPqWe5ed9dDb3yWuut5zfVIYr2w\nB1mlHXusBdQpipY+h1gYFjcDS0mOUwItXrF85PI4sYQkAxiJwd9W2CzqxMB4sunwdEMG7M/EhH1L\nJuxdXxPonCLqqA4OfL0GZoTk95r+fSiuoSTEaWbgtJUAGDUzMLj25iHP6pt6Yvz+7/8+/uZv/gZP\nnjzB3/3d3wEA/vAP/xB//ud/jsePHwMA/uiP/gi//du/DQD44z/+Y/zFX/wFjDH40z/9U/zWb/3W\nG99z1daU3WtMovYJ9SdEudmI9qOtAuAQY474KrVZYyo6Kd5rYARomj2q2ZEXhZx4bKxpb9FbJuvZ\nmIWQwVAUy+9aMYrJH99Ik8XVacLLPbnt+xDw+jBDK+AwWTy/HvCjl3v8C0tJ9sMMFwIqpbBsKtKM\nc4zNxaolIKKr6CkU9sUHPCGaRi804UQEFg3FiC0pHme7aLFoKhw5VeRqmPHl9YB1f0BTUYTS6+OE\nvq4QYsTVcSJTzz0dzMNsyZhQrhPePRkSNNQXiOjsQjIJHGaHcXbws4OZHLMwCi+R4n2Vzx3YLEZQ\nYcfGMkLVNCpTNUXucxbhBCSU8/n18N5rer/+/ddPYy8CkLsCTWyEvmEjzMIdOnvmVESJKwC0mdON\n9kOmG8pBODmPE4MYYlQpk/xTcaiLZlT2IMlVL5v199WUgv/JM1cCveXkZJhdinY+jRZtW8PUjiVc\nfC08a785ItELXTSx4s7jXO9+QfKRY8hK4Nk4T3uyVoBXeQo7WVgueo5CQ50dJueS23mOu81JQx+y\nElitMpAqbueSQiIsC8k+dz7iVOWGwvmcTX/NMbSXLCPZjxYDF2cCqOamhZhya2b60H1FjUxbGyrg\n7tfPxfpp7UUlDZr+O/+7AJp5CPB2YDOfhIDMDWXql2OdSUYhXgwly7GcrA0zSRyayqZ4c3mdCg4T\nfAYyXIDEnSPtE9nBPyX9JG+rls2TDcc3cwNhA46WDDNP7CdRGgPmiNKv32lHSNwyG5gysDLMHsfJ\nodIzgIjZ+sR6FTPn4+SwH2Zcnia8Okx4cTPg+Q3JSWTy+eow4eo0Yz/MZJznQo4vTD5BJjH+VgnM\nZEO/ukreADKJlkQoYz29PyGykSDF0Wr1puBQzo/bS+4KAdszc0el6xOL4dH9+navn9Ze1NZ0HlVa\nDPtlsJBNPadUg/Oz6XNfkEADrjUOnNhDZrcWx9litA1mR2x7AMTCNMQIVVpjoTUeFSwuGjoXTIxY\n1EkROEWX4jtH6/OQghkAs6NB83F22I8zdrz/iEyWBp0awtRORuZzZs3Ozqd0JImOvsOx7N2reLbS\nHhlv1WvW4cS9Me2tBnVFcbKICj7S7zMwaHAzUP95eSKPnqsjxahes4nncSJPtwRgGJaQdA0eLDs8\n3lBq3SfbBT69IPP1ZztKkXu06tAuGuopha3rAwCPEHIvd5pouLMf6D2m99llOZ3PXhhidE5mpjXW\nXcWedHWKk5Xa+33rnSDG7/3e7+EP/uAP8Lu/+7vp75RS+MEPfoAf/OAHZ5/7wx/+EH/1V3+FH/7w\nh/j888/xm7/5m/j7v/97oiwXa7No0sHZVAa1ziCGoOHD7NEYl6UKxeS+PAzHOV+4m9HiZiAzpevj\nRNpppagYB/0ZThP2x4kiQ/mgScigoIpnh+Rb7kHI4RISpfxmmKlZMRohRhwmi0VdIYJiZV/sR3z+\n+oAvrk+4PE5Ee4pA0xisuiq9eaTTMkSxVEo0NFy4Syzt+SuTASZFjYb8VKfGrCpMCwn1vz5pAhEm\nh1eHCcvLI2qtMbuAy+OEvqkQI732V4cRz6+HRJGUuDB3x2t58zrR+2p9Nvs5zfyeDTOuTtQELNqK\nTL9CoAclRGC0mI70OTel4/dENCXaWMKZxi4jfETTXN7yPDEFYGZ9wH/F9bsegfv1LVk/jb0IAGds\nQ+g7KUUnUduE1tZWODRViij2wsbwdGBKc5BBMjKJGmbHHhL0s0WbOcwOB/HHmG2K7poL0CBJpD74\nbOTDMGYN6GSp6T5NVETcjBaXxxmLZkLH8dM7BSjRp2tFwOnsELiJECTdyjQixGJfvut1FOBlAp1z\notBxcmiGmT7Z+fwzrYM7zrg+EC3y8jjxs08HYqmrtcV1koSSDy276bUpBlbZiMp6TEbjNNkzHfrs\nPCXOKPD7TWfPYeLzpjDwE9qkCyFPG7hxWbIPidxT67bGgj1+6spQAXe/fi7WT2svEv8G8WsRejGQ\nAc0IAuFKerMsITUloPHse+c450pnP6+uqageY1mnRK7KczvMHn3juF5jBq3O0axaARNCah4mbh5o\nCpop0db7ZJRLhe6M3bLDhgHilocMAP3s0RHQux8sDjzNk8lvYmbJPoS796F0XYr9iKIZQ5508oCk\nTcAlRQO2lUl7uQtZBii681eHCa/2pDV/yVPPy+OEqzJemanTCkjJKKU/0G3vpb4hUEnAItnbrAuY\nTGZgzC6wvEZDK3+GJBP+8O6dUIwTNU+O77rP7kpXuF/fvvXT2ovkzBMWlgKSfEnOczHrlNQJilz1\nSZ6ZQIzZYT9ZrEZqtvf9jMPYJMNb6zxMrMBmONy3KCijsFAKj/g1CXM+FGz62/f6ac6MjMn5MxDV\n8sD7ODsc+bXIQKFn2XpldAL0HMfFDlaGPz73iS4DGbkewgfhGAmQiZld7pLfCNVrEmkvgzLZE+jr\n6XNnBlgODA5dn2ZcSU1ymnDDQMIZmIrsgbHtKTXu8ZrZF7slp8ct8YwTNh9J1LQYsGvFSS7EjrGO\nzogMUs24EbBqyvWj+JYAUheZwui8SkbnYna+7UnO/Y3TSX7jN34DP/rRj958E+7YJP/6r/8av/M7\nv4O6rvH9738fv/zLv4y//du/xa//+q+ffd6DZcsxMhSnUnFjWRaIp9niMOqzjTUEx3Qe3tSd43QA\nmohdHSe86kese47k1Ao7H9A2FZQCnPW4Ps1swsSouRTJxUSULnZ441C8TeEMPKWbFB1uQq/2gWJk\nL08T2sogxojT7HF5nPDl9Qkv9xRT6nyA0opNAcl5v2tMfoh8SOwRjJQ1LlPgNH2Uw7mg8wwzGU9h\nZlZDCOwCzNPApkbfkgnh5AImH3AzzPjqhgqYyXlcnkhaEiMwOofrkyXnbZ4yHGeLyYUzZO2ua0TX\nKaOLVPw73AgV+zCmGMtKa4QQsZ0aqEojhohhcnh9nPDVzYkNsyZcnsgwS6Y0k3WcJkM/vzZ0Xy05\n61g2qUwZIzf0wJva/fr5WD+NvQgAm7YhARmN0cmoc8ETs2VHdLe+mamYdyZJM2JkMyOtYEabPeoi\nHTTLuU6TTpmsldGdxIqgYlqeKWF5yHP+IeWkNDAhRDgXMauAyjgMVuMwaXSDmMhVbGCnWPJN++l2\nokZFuvV5JrfrSwYuj5PFqQBaXMkWKd8DPswD8vSVKI+0T16fLLpqggKwcgGVmHqGgGHyxGZjTedX\n+yFFUV+eCMRMzBU+mOXZ/1CgR/Yr0b57H2G1x+Q0DBcPqjiP+rpKZq0xIullj7NNkyVptEabpw20\nF0nmvEHfkpRk2bKpalslML+SmLf79XOxflp7kREQQ2VnfX2ruZR7XWmFEEPCYG+/jhAUgs6TQnlt\n4o1DUl5FqWFcj7VVlZixUaapLcnfOo76awwPAwrQVikHzCSvIwKlP5suStzeUAydrocZu+OEDRsG\ni98OzXwjrKMm5DgR4HEzzDzVKxhZoQQw7x6olP8vhAxaTqmhsaiGrPsfrUc70P4I0ci7gNE5HAau\nNVlGRvpzqkmuZJ+cyQNDopUFyOwaSkChaOUa277FbsEgRt9gxdNgMYYvz4qJGRgkKVGFh8n5fRcB\nliLefW4oIPmY6eI+I1YNrcTguC+Nfi7WT2svqlnqDwBGk3l2RI48JbmFRK7mukCY8tKTjFazfKPC\nTTNj3dW4HmpshhmbvsZhqrG2NToXgJZfs3h1aZKZLTmtTUCCWNRGTNBPSyngiMzImKI/Y4GOMkjl\n3nHd0TBh0VToKo06yUpYMRGYdWKFbWDJ+FOSNlKtVspd3z3ckT08xpg8giyDEiPXZUh9U6D3QnzD\n+DWJWmEoQIz9SAOf/ZiZrJM934uShKQjAOPRpsfTLTEvPt0t8OluiU9ZSvJo06NdNqQKaKpUG8LT\nn7FggtDP5nhpHjiLpGRKIEpZF+kU8LDuGmw6BjAWnAzI6YBd/X6G6k/kifFnf/Zn+Mu//Ev82q/9\nGv7kT/4Eu90OP/7xj88ehu985zv4/PPP3/jaV0eitzSVxi88WuN72yWMUdlXwjrcjNRw3jZ3yXoo\npgVVhP5cHWes2gmLlhoGBQXnIw6jRc8gxjB73AzkJv/F1QlfXA9Jv3h1zIwMORzlHtS3ior04MQ8\nVRUKpVAqT7MlDwujEQGMjrwyJHpr4ligpnBmrY3JmuvZoR9mAjJmh/1hxNVxwmG0yeFVHpIM/lAE\n4tVxwukwYVFXQK2BiYzmfAhktsfZzE2lybSO3XivTjO0UpjZ8FMAmNkFHFhztR+y2/bsfGoI3nWN\naCOgwuY4OTTVjMujySkjlUk00sE6rPsGbUWAxkkSVG5Ib/riJgMpB36/JuvJBwWAOcs6Jp3XbtkS\nNYkLpS+vT/gfl8dU0Nyvn+/1TfYiAPjD//x/cxMd8Z9+5RP8p198fBYPuuD4vWWT86vpEFNwLGdw\nkQ7sFPcLQOKwJhvQ1hyVBZUkJTIFHBi0HawrNKbi+P0mmCrrLip5BIMYCFBOpq82GxDfekYFTNmP\nFttjg76t0gE+O44RPU7J82FfHkopLjC+8RpSFBhPao7MArk8TmiMAUANyrKtUTEDwfqA0+RwPZDe\n/MV+PKNrXx6yceZxdvQeeF/QOj/sGtFrjPCR2CcSRKAVR0kCSUYys8+RYdNDH+lsmJJxFRmEHSeb\n3rty2lDJ9LWu6IMPbUlc+X//5RX+r7/97+hajnS8Xz/X65vuRTQpowKxMmTEmZZS6dnyEZQ+ETSg\nz4GMCN7OkI0fz2jXEPUcm5mn+POKE5YKKUPIz4CAb109syk6fT2ZbmpoRewDGbLMLiBGVzAfiqKb\nn/MdF6srMddj7yog11bUcJDJbikvERmpCwE+EGGVepz8xNOgRxEbNGZZhkyI6Xct2B/WJ8BZ5GSW\nafHjnJkYV6cZV6cJV0eafIoXzmmixKnkh8NNQ99UWLcV1kU6027RYbdsmH1L4GZXVwwMyZCMmkUF\nalwar1FZnc8YZCsjqY3F7PBtAIaY6WtVJCXw95e960MB4fv17V3fdC/6y//nHxi8B/7P7z3Cr/7/\n7L05r2VJdi72xbCHM90hx6ou0egHQXhogOajIRkyZZGGIBAgTYIOXdJrgIT4JwgQEG1CFv8CCVkP\nkEFTEA0ZZHcNOdzhnLOnmGSstSLinLxZmVVdXa+78wZ5K2/ncM+0d8Ra3/qGL64BiIdUkWcII0Mk\nJiTtVlnuKffaYXZYTRabccZ2aLDtZ/Yda7HrPTZdQNMGDmIAAxmQ5gIrKLzk55YlHKnI6gSEEybb\nwNN/2YtCcvl5zy5mifp+arKppKQeSjoK7YHI+5fIJiQydGYvs3zvpW+X1wNlj5L9KCR5Tr48ZiKG\nb+cCBhv4ZqimCwAAIABJREFUnhXGfbFTGHlvFHlw7TkijFWpjchhgIbYF+uGJCS7Hi8v1/jJ5Rpf\nXLOM5HqNz64YwNh2QJaRcHKdMP1dwLx47CePO/bjuBmoN6M9kVggkydGWu7R2KtwJWmArBC42nS4\nWne4WnX4xc0R/9f/+2VOoPzQ+s4gxl/8xV/gb/7mbwAAf/3Xf42/+qu/wj/8wz88+Hdrfaes//G/\nf0lIi2zclijNMhEcFo/NuKC3BlaRZ6sAFz7SBZinmYvH/bSgY+f7jicEMQKj87gdWkJyFDAtAfcj\nSyPuB/zyhpykXx9IXrKfyiQtpVMzLKM0xW6lolEUOiNRKCNidNS0eEL3V3wgIRVa5n5eMC4EKJDJ\nU4l0JeMW0lrfHGcYa6Cthps9vrkb8Wo/4Xagf+99aW4iTwePs8fNMOOb/YSntwMV0a1BWAJujgvR\nrEJkxpbK9CQfQm4glKJD+zCR/jUBmUEhtKDRMV36nfeITQ1TMcvLdKuUKG2W8+Tr160VTzu4mdr1\nBERFBjVuOff4y7uBGBmHiT6vcTmZeBjWnq9ZOvNkQ/4iEgt0sWqxag1++nwHpVQuqv7v/+/Vd70F\nHtdvyPpV9yIA+N//t/9COzxvzBiWbMbYNwK2CYDRYNU69IvF7GPFxqBDR/HEDJDDj67rxormu6Zk\nhqzRnLzPh2Lx23h3ykq0X3k99GvNQpADlIrRmL055c+QiCYsIMrADcXNsGRatzBGfEh5WnFzJHnH\n3TBX6RvCxDobhUjDEIrUbj+RXrNhlpkLdK+vGgtj2DzT0x50Py54K3RtNqh6vScQ97Yyy5vZUKwG\nME4KmbP35+Qpyj4OUKqJj1Aq5BQYypWPWLzJhoYKyNp4d1ZAjGxCGFhGogTAYF8eAcM2PPFe8Vn1\nP/0Pn+F//S//CZdbomv+7f/5Xx+8Rh/Xb/76Ifaijg2AS4MJ1FoBYhQo6FSiwVXSAM6AjCTXeCTZ\nVGSpaSL9uTgoKCAnfYhXw6qhCHeZwgaRzM5kbixxxyWpqJh+Gq3yIEho50GaHpG2Mb38flxwW9WB\nEk8v+w9Ae5AMaEY2CBRZ2eRFZ00NwTv7UH7PaHIre+7sNVqnMRjRl9M+PS0FwLBM5RYpzOziCW17\nPy3Yj47BC8/T2YA5FH2/NaUe2XKM/NWaIgyf8HDlat3hclWkJK01We4qUmW9iL9ShNEhM/1kD4tV\nLVqSHE6BiAxg6NN0OfFJoedbJQQmYBmWB6/Rx/Wbv36IvejP/+f/nEMYALCpbHVfhMJoKkCGyDxd\nMagUuYF16EdDCV3txJ4wc06g2PQWV60h48hGA1ahRJAJkAG8ePA1yJckfVRSN96LfEgYU8jsUGKu\nkzeg7Hv1nib3B/AucFNkNJW0JJT7TyR95+v8vvUhYfGJBygKUB4xkaXBbCQAQ+Kv0wkzxLHsRKQu\nwurNLFUxE8bpXnS5anF9IiEhAOOL6w1+cr3BT642BcDYdEDHPhhEVcveZXERRt3MXhwk/6Vo6Rn7\niZlzS8g1srDSVg15ge36Bpdr2hev1sRMu9p0+OnzHf6X3/+9fP39H//y/3zr9f6dQYwXL8pl9Od/\n/uf4wz/8QwDAF198gX//93/Pf/Yf//Ef+OKLL97590+3PZ5sOnKGZQqd1dQwOx9xXBx2Q4POGj5M\nCoBBxb3LkYQTN/2N0Rm1SeBGfKaGuLV0KE5Cjx5mvLonuvKr+xFvOXpmmAtyR0a5Gq2RrPMyYfU8\nWSi6KCrkl/zcqDnuLMWUyr9xPFVYeFJR4g5Z4+QJiHh7nPHV7QAXIqwmKtaXtwS43BxnDLMnJgaf\n2BE08Tyyt8VXdwO2ncUSAlatxewCvrknP4sMZKA8Phj5m30AZip2hsVXxnYkOVmyDp2RPaVyNG0r\nefOq6LiEcibu4jJZOU4+U1rlQPaRmoK7ccGmp88+JtKh7ifHkhKayr7lrOPD7DHx81HVzbFbNbhe\nE4Dx8nKFZ5xvfLmifOOm2pTH5TGZ5Ld5/ap7EQBgWgDL22AgGjTZY+isG1+1lrTjLIHrG49x0XBG\nIUSVi2gXYokTFCq1DXx/6BOvBTHOowIglgMxe9+8S5NUOKUB0+MU6nAdMxwi0f0ST+oiNzJLiHAS\nIcq07ss1NRNiKqc1MeOoeWH5F4MIBzavnNk/6JwFIcZbjimPA5totVZnSvSRmWrZzC+QDn1YPPYj\nSc1uj3NB9oc5I/vCWDlnYBSzwer9oUFsxQw7teDKrBUg0zZKLFtCG+KDZsA1vVS8TE5Mq5TsiwSE\n9W11DTUWbWNO/FNSJCDlcf32rh9iLypT8jItV5XjfR2rqRV9+RiBpJEUbRgCZNL+gzwAEkPMbF7O\n947sdZk1xP4UxNTUWQ469QHbnqV1bTEEpb9rMqvDak1yU75HheGQAQkvvhgN9qMjz6qO7osaRJCJ\npOjSF95LpFg/9ceInDL3bucQ66EKN16jC9wYIIOtuXkxlF5SP/bExp8DU7QPbDwsHj0E2sRcO1pD\n973EKV+tugxePNny17rP++6ma4itxwwYGYwZxftwdXZkkDV/pjHXx9mAueqgTgAMXeLmM2vw7Cwh\nEOORivHbvH6IvUgATvGRk/uS5ByFnZDrF8fMDGFHMRtTvCnG2WNvHQ+GLDbddJLOI5KyVcusRJvY\n5FNADHpSKwAvzi5PpQogl/dOAermwtYOMSElYpA6OcMXktHSENzmSHjLnjOF8VT8vWiQUbxAlrpm\nSwISv3sPibQtJpU9FZ2XgYvnvVazhCRkIEWhSmfkPWwJpf6QAVgGdXkvkkG57EUXHKP6bMcmnlcb\nkpBcr08BjF1PDIy+oc9CNmMGMLA4DGwJcHOcs7TuLddsd1KrMaCdo+arM2bXtxnAuN50uOZfr9gr\naMu9+3kS50PrO4MYX375JT7//HMAwD/90z/h93//9wEAf/RHf4Q//dM/xV/+5V/iF7/4Bf7t3/4N\nf/AHf/DOv3+y7fCMgYyLdYtNJbsgRoGjBBNhVaSCyAtoQFMFRvmUZ7MpzZM0+pD344J1Sz8HoCb9\nkN/4Ca/ZPO52mIki7csh1PAhJFOH1tbxO6dO9pMrH5RPCcF5uKAwc66vMA1qrRiATGOWg3RYCMD4\n8naAAnA3LtBKY1w8vtmP+PJuwNvjjMPsSF+EUqzMPmaWyS9vjrBa4TCTjtWHiLdHMua8GWZicnA+\nswKZO9XT2ZhSpk8LAinFiFC3BNnr2QSxZ7q8YWffmu40LpQg4yuzHUxyU4s3BQE4d+sF664p14MP\nOE4edxOxMd5UtPbJESMFKDeqTDyebju8uKCcYzGnuVpzlKGWn01A1+P67V2/6l4EAPPg0LYcpRcT\nR49SKyBFX291ZmTk4r0xWXoWfcpN8eLLEeZTQhco8eekGc5FdUH35XCU/a0+ArViLTNOm5vMHIA4\n7st9mgqQwYd2SeFgicdC4MTNuOBS0lfaJrPZEgDPBbyYgt6NC+4miupaHKUSSCqQrJSZGClLSazW\nWeI3LgF3IzVK1jDoyQw2iee65ynnfeU3kaedPiCG02nyOU26fm9y0RCJhl8DH1KceOpYqr8vIJNQ\n5SvQIxLgIo1VKWL4+VRMNymOVnzdrNgcsdGVwXAkV3frHkXov83rh9iLcnOZm0ydwUuAmRgRCFrA\n+whAIyHCQJ94eQkZi4Y/Ku819T6T4835sa1mQ2z2a2mMOamphsVj21tsORKPDLMJlOu4+G8MMTMH\n5TF6D+cTD3liZjKJP8Zx9rSv8iRUzEVPAN/EJsm8R8gUVOjilIrAcYuC4PASgDe7/usI7T03DVUN\n6UJuWuReF9DDhZBrPWGijmzgKwbDMRWJTpsTrogmfblu8XTT4QmzQp9tezzZUtG+ExZG9V4X486A\nBAKA6NxQlREgvR/5s+SIy4ekdapiXjS6Zs0IExYQlKw0WY8gxm/z+iH2ImmCGx7mJIDZWTKo5GtQ\n/DAeYiZEn2VRowtoZofOlsGQePGs2X9s1Ro0rYVtDE3/rSZZifwKulLPGRkCxAmDTa73HAevVG7w\nY0qIDDo4BgxaFzA2Bq3xlJqZQQx10kTXceyu8rLweVBb+RW+Z4k3T1AJChFOAXAswY2JagMj0l8C\nb97Zx0IBkBZHNZ34kdR7UWPJ323TWVyuW1yvOzy/WOHFRY/PLosHxufX61MAYyMARuWDERPgyN5g\n4SSUtxVT9vVhyv20MNSysgGS0kY+GDveG6/WBdy93tL3l8yaXzek0PiY9a0gxp/8yZ/gX/7lX/D6\n9Wv83u/9Hv72b/8W//zP/4x//dd/hVIKP/3pT/H3f//3AICf/exn+OM//mP87Gc/g7UWf/d3f/cg\nVemKIz+JkdFXbAkFx43ltlvKRJA3bXJjLbqrkX0lZh+hZ58jowT5308NSzqIUTCzCcn9KA6uZbo3\ns3OrBkfPdNQQ1whhpllHiVSlgvu4kKP97GL2qqALPBS2gUwBzxiPYp41LmQ6+mo/QmsyBt12Flop\njC7gZpjwy5sBbw4TDrPDwhNjeb2LDzjMC17vJ6xbi5ASbo4L+kbDh4T7acGrPV1s9yNNSUKIp88F\nYBQv5E1BQIZ62tlojb41WHdNdtvv2dlXpDwuxJzH3BoHPRFuIU0fXMgjo5jKlGU/OtrILOnmCdwJ\nOQXgdlg475iAI2GEtHxzXKyayqxmhZ9cbfDZ5RrPL1a4ZMCsMTqDKffjI2Xyt2X9OvYiALg5ztiG\nAqQ6z01toubBGg3LB1tnT6ePrQ3wUefmVppiFxKAwAdmgos6H0oKha1AxWcpRMO3ABgyDTmJOKwm\naCFRMS+AY62Fjyz7CIzil5ixhrSMTOfuW4suyycUs7yKhvzAuktJ4XCxJBEAZW8jwDZgdhqDJrPT\nyHK54+xY+15M/Gon83H2OCwex8ljWNiDgw9rFwICP4gc1HnCaKQJeZelIlMYFSI8Tve0mIAUIpCK\n50CMCd4kLvQDFBQkmjFINCMXLzUwrUCHdWM1Xx9n02pL15IxZX+ViO4YH5kYvy3r17UXlYl5aeRl\nWi6LBiIKPiboqKBVhArAkgjQQCyMoMTSAvF3aTPwFuE87QUhlOm9AHAdm42vGsPMBJV9f4bZY9c1\n2LBZdmlETAbtWjvj3jjYmWojkZfQFxW2i2GZaqPRziazP9pKniI3cjbAy6yMkCnhMvV93+2Tp6iJ\narJFAWCvDucjpg88Xq37z9r/871IVVHKHcUFXq7azAh9uuvwbLsqde+2Yy+MFquOdPhGlf120oHZ\nNtLEJI6ErT872ROpiQlVE5Ovp2p/bIUpw2yZovsv11ZJlPrOt8Tj+m+0fl17kXgYkAkwNfWtpQZb\noTTdnhvozEpglgDdlyL/F088jnduZABKwL7sIT1Lyi6shraaErsUszGMAroG4BpqDeAlP/XMwuDz\n35i6LtCwZmHWVJG6lbqIwIzZx8wst0bD8s+zpjLQRWG4xcw2iVk6L9I5+nvvqGy53wFUKnJA+Iho\n6P02IRHQWrFKgZLwSI9T1R+xSmqq6yJN3oCrpoCp18zAeJF7I0oh+cll5YGRAYzKyBMJ8AnwHpgd\nAiefvDmQV9qrewYx9gRiSOjCuHg4HzLbr2HfpU3f4GJNvkCZmbbp8GTT42rdZasJYWH4j6iLvhXE\n+Md//Md3fu/P/uzP3vv3f/7zn+PnP//5tz7gtiOk5Qmj0herBm1joTVNCy4Wj01ns+GbD0L7oezc\nrBvnQ4hkJR5qBpAKo+C4eG6sNU0SgjipEh1QivFFAAyFPIW4YP3i5ZpMIddseEXpI+ndiaHROLI+\nOkcQggCGeos4x+eE1nSYSTKhFTX698OCviUQY2FTUDHXG2ZJ46CfJq/tMBGTw2qKTt31U457Pc5k\nvPKmYp7UxffJ86uQRPlTopYpNqmqpgwchyNRgQI6kTSGs4vtDKM1AwaVa7APSFNp+kQatGpLGoC4\nCcskWIxrZpb9yM0hPhjXmw5PNz1e7AhplMigFxcrXKxbipTUDGLMDo39OKTvcf23X7+OvQgA3h5m\nuBAp0UipfG06BgHqyXrLU4TOkhneJL4uWkFHjv+ikT2QNGnSDTEy5GCSldMxMkvi3SmaFqo3H8Z0\nwBZKsFCiBaUPKcGzzKMAIyXqdIohF70CxO4rPWjXGG4iFBSzqoRBNjP9cnSek1SYiRFPzT3LxIDe\nx0wLD+Rh9I60JlMkA/98Mc9iA78KKEiowAtTvHXEvbsGeORnZyZZSCw1IQlJPYUW1kwMEYkn2z4m\ncmXXVZEfKyCDpyI1E0Ux4GQ1XysMZnSNxonWFooHG2zcp4CPoU0+rt+M9evai3QFYFhNZry6AuYE\nlJPBjg8KS1VhOM/MDB5QSA3iVIQNNI1sveaG3GNylvY6MTOvWBmtpWGF+FQksE9DlpXIkMdmMKOv\n9pG+mdEOdH+K/ENi/jyDGSQvUZyWRPdxw7Jg2VepYapYU6H4bdTMNTIyfXcCKlKyEBIciJkWE7Fm\nl1D2UdobimZdJqvCAHbxNFZRinNhX/QcF1gmjC2ebno82/V4tlvh+a7H0y0xMq7WBGCIdEc8OJwP\nmBQBGGJoFyPvEwxgTM5j8pLQUijkjllx+Vric8saxewvBom4JrYMTiktwA2QkjB8HpkYvy3r17UX\neR+yDEAADIDONonmlfpF/DEoxYdBjCDMc2RvHEkbalmq3wuYUdcffI2uDbMvtAK0LYklrc0bwgrA\nS5x6YWmQbIHMzHWWwUjNNCqS9AsrI0Qg8nlvg8KiY46hzpIUnEuuSnx09qVJErX6EUyMJL5lCQkU\nSxuUgtIxMzTrx6sfI4SIUIEasjdKXSQs+RUPmCXg4Nm2x/MdARifM3Dx+VWVQiImnn1TARgAQgIc\nJV6mYcbhOOPNfsar/chejeTX+PYw4XYkYsCwMHCdShpJz4DK5arN8jpippHk/8mmO/EutNy3fwwp\n7Hulk/wqa9WY7Ep6uWqx2bRQXQNohSYldLNHb00GDGamHo4uYGATEwEyZAIq+eSkHQJcoEg/yT0X\nJ/7ZBf5ZPstAUqIPv7Ma687iStBzRs2v1kT5k9xwH9mAblpwc1ywZldta8gQcOLn58O3O9XmxsIH\nimYEFQnD4vG2I1r36eMREEFASflwYypeIjdHmgqLsahhUIGiTYmafc908NlLAf4AkFEtzboqoYBd\nrBpcrQU963C14YlCa2CURkiUdiIGpTWLBQoY5pJsMPnAk1g22mFqasNTEXJHL1nuI0cbCfhS670u\n1wVtlJv15eUKn1+t8WTXo1+3UOx83PiYZUaP69Nebw4TXIhYczJHSshTviyhqgpC8YBpDB+4XlNh\nrVXO76RfIlKgvSeKtvGEIVD2gIeiEuW+M1zYS5JRw9NKoQMrBsuFbVC7hi+s3XQsd8hgBzcUJOHQ\naK1jOrhhyjE1T9JAyMRBGgeZuEghcE7hjsyimlVhQiwhYJh5wizNCVJmj9Q/d3mA5QAgu3SX94Fp\n7KYyCq6KcmlEFh/h2BRP+Zh9iqTZy887EcCRkmJASwmL9eTvZFPn6pCVCYgAGPkaMaWQkmYpx067\ngEGr7FP0uD7tJaaLAlpSEV703iI3EO20Z5CNkoh4c/Exy6dkIiheOKbychmXgFXrcy0kNZVEloqs\nVgwnFTfaMURcMJCxZVPOdXdmXMveL2IAKhHN41IaCJnkivSseDaEbEApTFZhQtUFfW2wnov5B6af\nUhOK2XGCQnS032R23NljhPrnC1U8JaQKSDV1w9BZMipkPy5pGmTyKd+TjKTjWFmLpinu+ylGTIoY\nNiLhIRAl5DhFMe6jgR7JdEWKKA0UUIGpDGC01qCT80r8yzQZ1tfATUwk+SOZ0uP6lFf2vEqJJUlU\nFzTMkJe6Q86yfH6z1NJV12XtJzEuAVY7YmRkkN+gZaBfAM2XRqPXuriZNzgFMgAACSsAzwGAAUUN\nlkop3kOtPhl2NEbnQYyrgQAepqpIEitXSVEeGjJI3VOnQEk3db4Pna+UgICIFBV0IuZFUAoqFukg\nvTph8KfMNhPfM5F8EXjBwLOh95LMhC0uViRbe7qjJJIXF2t8drnCZ5drfHbFUvvaxLOWkAA5HZMA\njAXDccHrPaXFfX3HyXHCwuDkzf3sMC0hMyiMVtyjNdw7ttlS4mkF7D7ZEDuNPBFpX3KB2LMfWj86\niJGdsBuLvrNQfUP0lYYiXHTrsTYaLxJN5ySHVtgTx5kiPmemEsYqrYSGoGS+NrnAPg3iqxEymi0H\nNgEYIOSPAYxMublY4cUFUQB3q5aYBswOOMwed8OMXT+TnpGzvcVZnFY4mW6cr5SI5qlAUWRCqT5M\nLk9ElSommbmRZ7aH/FwBaMbFQ4NoW/uZzE6lryIjukrPKSad1c85X7J3yOd1bgzzPE8XyKBq3RJo\nQlGpAXfDTOBPcx6T4zDMKWu4KNmFmpnZRaasUQNVjPRCbswEHBLgadUaMolhytTTbXluL3ZUPHS7\nnrKOOakGS4AGKJv6cX3S69V+4olgg47NFmX/kGaagIyiI26MQmsr6qHR+V6XwyUm0RgjFwL1XVAf\nRvWhJ/edYQCj5eKzmE9R4y6Pm70VUmFiiFHozMZPc6i0qpEbiJQQUoD2EbNTGLWCMcXQKgMkKH4Q\ndTESYoJPhRFWrxQTPMhYVJ7XrFjnmQEMabAqOmbWlhZfjwIOVGwYa9mXhDSfxVhYgwkkBcBgsGD2\nGloFKBCYAU8SEl8BEfI6qYnj5rHaIuSzFJp+/ZnpuvlkNotERtbvZ23ONTiPiASj9KMO/XFlw2uj\nCzCXPQxqiWciuZMPESaQZ4LhdB2ArkuHIk0TNpXRAZNXaJil2s8GQ+tx7Dw2s8e0eDbw5hhXnrxm\njTp3Lk1M6BePLcttt5U536qz2LQiNWEfoXbB3WByDGlhf8QMksaY4JWCUzGDnHUTIa8LOGWkZMlc\nfPj+odsqIUCYVIoahgxelJ99+nOre70CKmtD874hWe2OB3KX6zYnoj3f9Xh+UUAMGoh1uFw1aPuG\n3lPNkx3S/MAwW0y8Q2b26xDpMv1KjN9hkYjHKiVKnqMuYHtvNTo2bBbJTmbyVYCvmIUqsCzpcX3S\na6oGFVJv0zCyxLUDLGONldRLJE8sKRHm1JxCHjAfF5WvUWvES+d0GGG1xjOl0ElBBAANUy0IYQVS\nQ4yMlPCsbuo1DR+ItarQMJOEZJ4OzaxhNQGCLoSTlDO531US5uaZWTjO94xSv50z2M9Xqv6TEpAU\nENXp49T/Xvaj88eRpVQxEW+MRt9S6se2KwyMJ5sOz3fUy75gAEN622e7Ht2mJQaGxLyLhCSkDGBg\nWDBJ5P3diK/uBnx1NxCIcT+SSoC9MOr+tE6MzM9nW/WP4hHELIzdiqwbLLPlfQgfVRf96CAGkDj9\nQ0FZQ6iavIEAmbgohT5GPGVjuP3k2Mdiwf3U4jj57HwaQsoxm95TtlRMCV6LsSay34MghnK4FzmC\nwSU36M8vaHr/BVNtnu9WuNq0WLUWRqmcfPJmP5GrNHtB0Es7K3BdoGL+gc8hgQ6r5AN8KjnqjfGZ\nTqoUa7Fjrc881c0TGBIxOXCiQISZHD+n4ikiNHPv04PmgedL8SS4zUBBg+t1i2c7Msz8PL8/Pa43\nHUmAtC5skkOLDZt0Ftp7dWNWUp6FJ7pEmyyRhjJB8YGeewjV55Zjg2gidCExPZuWdVaE9J2gjJJ1\nrBTgI7R5NPb81NfrwwiJEewbkx35JVo47xcpgfYuMtwzSnPTL0Uha8ureLvcFKtyDst66FACakmC\nymyP0gyY7OIvQKfRJZJQmhWRZkzsAySmdBMnaWRD0pTI1DdQBLLyIftv5CJf1c+5FLzSQDw0/aSh\nJ089I6WP4H0/q5qsnoM5MpWWiU39HtQGq2KWKdRokepkB2+jYVxg089UHh/FLyRVz18aH6SEePbB\nva+YEOBJqKuWp0E1sC0TGxeIDUjThsIMeVyf9hL5WK3nFnlXifwjJEPkTE3QMCpkkEMWXcPlnA8h\nYVERRgVY7UuT2zqsJpKEHOYGW94nHA+JEiDFQAYyFBJsa7FtPda95ZQBYmJsOott22DdmczOWB+Y\nlTEaHKzDcSH2h6SWhHz/M2AQUwZzSxNRvTZUe+wZCHm+6sYhJCDKHlABGPJ+vbdZQOVLJMaEDZkR\ninmn+F8825Wm4dluhWfsh3G1abFZNTAdO/4boucTgAGAJcKSfiSx9sfJ4chSWklFOS5kbE6JEKHU\ns6jZYKai6xe/kgyMKZ5yo7DKfGC2TXoc7nzqi4y021z/CBtVG6p7SrJikYs6rtN9xaR0vkguKYYc\nmYFohqUYzsoQQOt87mul8FQptIAUC6XR1or2ow5QMWGdmJEBAHzuijRP6qjGSOIk/XqcPSavySC4\nqolyn8KPy1Cf/OgH17ftQSd/r/pL4kP00L/8tp8nklkBLzqr0XNsKUlIWvaeLHK2F7seLy5XeLEj\nMOPZtke36Wi429oCUqdEHhjuFMB4fT/h67sBX94N+OXNEV9xYqZ4YdwNS0kjSZXJMSeRXK2JcSF7\n43MeMD/l/vFyTT22FYZ8iIATBt23rx8dxHAMOogmiKtVehO1IspQTNCuwXZFzenFqsVV3+Jm1eKi\nb7Hv+SBcQr5J5EYhinOE17UxEqHw4Yy2TckDBtu+xcW6xbNth88uyPTkv3uyxRfXG7y4XOF63WHd\nFt+O+3HJLAOlwHTpmLODiemh4LSCCnhHslGvCCCGhMDTUpnYGU3UKKBMAGP1GmQllDhFoY0qlGln\n3SQ81HQ8tGrkUSYOm44+i6fbLss0vrgmz4knmw7broFh08zj5HC5mgj40SWBQMCIOg7MszRGPrfa\n0AoyIUiVDhVCnSLNLt24Fhd9i4u+wRUXFZfrFuu+ITOg1tKX0XRzME3t22Gcx/UprDeHOcvWiFVF\nm6ika2SatUhLUBnwqRLnZZVCVOqdqD8puFV1YL3vgCoABkceCgPDUvO+YTNdomsbdI3lNIBK+hFT\n1kqjRkxEAAAgAElEQVRPnEIyzBSLOpxliWfJRpIIUt6Lzg7sc/Ovj2kcpBmJSAjp3X8v78M7zYJC\nbuAaY9A3msELahrWORmBQA1JNBDgU0Bdx3461Ay4k6kj80R4yqHJI+MM1I38Waezz+2dz4zfHyNf\nwsjT6mTaGVMdtU1gUYipkjA9ppN86kujMBCsFPZidlmlSQj4Jw3vqYcEAx3w7HpfQLoQIjGidIA1\nnhN0iNlEsYeOAQmH42yx6QjM6JKt6jTWqccE1VmYJeC6MZwuUKQl6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PawWmN2AUZHeB3h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\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H5tZQXm/X1PlN11B/rEeGB2AGeM3kqOsxT95gEkNaBDjw3QR111GTxbjFPU+0aio2iNAS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NAwdBZbsEiJHJ5DytgSsTHE+V20NeIA/xgSppgrKu0spQP0BWb0eAwJ121UVEhAENHlyMM6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\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zSrWWxAV/ZWLIjUeaVC3GVoVRcv8VyOOkENnJM2ydAOi9WcYeGERyk0JVmnjUX0+MH0Z/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\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This is tableHead
but thiis the
bodyof
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This is tableHead
but thiis the
bodyof
Thetable
" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] } - ] -} \ No newline at end of file + ], + "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": "3.4.2" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/tools/tests/Markdown Pandoc Limitations.ipynb b/tools/tests/Markdown Pandoc Limitations.ipynb index 529872f..ff232bb 100644 --- a/tools/tests/Markdown Pandoc Limitations.ipynb +++ b/tools/tests/Markdown Pandoc Limitations.ipynb @@ -1,2522 +1,2691 @@ { - "metadata": { - "name": "" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ + "cells": [ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**WARNING: This document will not render correctly using nbviewer or nbconvert. To render this notebook correctly, open in `IPython Notebook` and run `Cell->Run All` from the menu bar.**" - ] - }, - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Introduction" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**WARNING: This document will not render correctly using nbviewer or nbconvert. To render this notebook correctly, open in `IPython Notebook` and run `Cell->Run All` from the menu bar.**" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Introduction" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The IPython Notebook allows Markdown, HTML, and inline LaTeX in *Mardown Cells*. The inline LaTeX is parsed with [MathJax](http://www.mathjax.org/) and Markdown is parsed with [marked](https://github.com/chjj/marked). Any inline HTML is left to the web browser to parse. NBConvert is a utility that allows users to easily convert their notebooks to various formats. Pandoc is used to parse markdown text in NBConvert. Since what the notebook web interface supports is a mix of Markdown, HTML, and LaTeX, Pandoc has trouble converting notebook markdown. This results in incomplete representations of the notebook in nbviewer or a compiled Latex PDF.\n", + "\n", + "This isn't a Pandoc flaw; Pandoc isn't designed to parse and convert a mixed format document. Unfortunately, this means that Pandoc can only support a subset of the markup supported in the notebook web interface. This notebook compares output of Pandoc to the notebook web interface.\n", + "\n", + "**Changes:**\n", + "\n", + "05102013\n", + "\n", + " * heading anchors\n", + " * note on remote images\n", + "\n", + "06102013\n", + "\n", + " * remove strip_math_space filter\n", + " * add lxml test\n", + " \n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Utilities" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Define functions to render Markdown using the notebook and Pandoc." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "from IPython.nbconvert.utils.pandoc import pandoc\n", + "from IPython.display import HTML, Javascript, display\n", + "\n", + "from IPython.nbconvert.filters import citation2latex, strip_files_prefix, \\\n", + " markdown2html, markdown2latex\n", + "\n", + "def pandoc_render(markdown):\n", + " \"\"\"Render Pandoc Markdown->LaTeX content.\"\"\"\n", + " \n", + " ## Convert the markdown directly to latex. This is what nbconvert does.\n", + " #latex = pandoc(markdown, \"markdown\", \"latex\")\n", + " #html = pandoc(markdown, \"markdown\", \"html\", [\"--mathjax\"])\n", + " \n", + " # nbconvert template conversions\n", + " html = strip_files_prefix(markdown2html(markdown))\n", + " latex = markdown2latex(citation2latex(markdown))\n", + " display(HTML(data=\"
\" \\\n", + " \"
NBConvert Latex Output
\" \\\n", + " \"
\" + latex + \"
\"\\\n", + " \"
\" \\\n", + " \"
\" \\\n", + " \"
\" \\\n", + " \"
NBViewer Output
\" \\\n", + " \"
\" + html + \"
\" \\\n", + " \"
\"))\n", + " javascript = \"\"\"\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n", + "\"\"\"\n", + " display(Javascript(data=javascript))\n", + "\n", + "def notebook_render(markdown):\n", + " javascript = \"\"\"\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\"\"\" + markdown.replace(\"\\\\\", \"\\\\\\\\\").replace(\"'\", \"\\'\").replace(\"\\n\", \"\\\\n\") + \"\"\"');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n", + "\"\"\"\n", + " display(Javascript(data=javascript))\n", + "\n", + " \n", + "def pandoc_html_render(markdown):\n", + " \"\"\"Render Pandoc Markdown->LaTeX content.\"\"\"\n", + " \n", + " # Convert the markdown directly to latex. This is what nbconvert does.\n", + " latex = pandoc(markdown, \"markdown\", \"latex\")\n", + " \n", + " # Convert the pandoc generated latex to HTML so it can be rendered in \n", + " # the web browser.\n", + " html = pandoc(latex, \"latex\", \"html\", [\"--mathjax\"])\n", + " display(HTML(data=\"
HTML Pandoc Output
\" \\\n", + " \"
\" + html + \"
\"))\n", + " return html\n", + " \n", + "def compare_render(markdown):\n", + " notebook_render(markdown)\n", + " pandoc_render(markdown)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Outputs" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "LXML found!\n" ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The IPython Notebook allows Markdown, HTML, and inline LaTeX in *Mardown Cells*. The inline LaTeX is parsed with [MathJax](http://www.mathjax.org/) and Markdown is parsed with [marked](https://github.com/chjj/marked). Any inline HTML is left to the web browser to parse. NBConvert is a utility that allows users to easily convert their notebooks to various formats. Pandoc is used to parse markdown text in NBConvert. Since what the notebook web interface supports is a mix of Markdown, HTML, and LaTeX, Pandoc has trouble converting notebook markdown. This results in incomplete representations of the notebook in nbviewer or a compiled Latex PDF.\n", - "\n", - "This isn't a Pandoc flaw; Pandoc isn't designed to parse and convert a mixed format document. Unfortunately, this means that Pandoc can only support a subset of the markup supported in the notebook web interface. This notebook compares output of Pandoc to the notebook web interface.\n", - "\n", - "**Changes:**\n", - "\n", - "05102013\n", + } + ], + "source": [ + "try:\n", + " import lxml\n", + " print 'LXML found!'\n", + "except:\n", + " print 'Warning! No LXML found - the old citation2latex filter will not work'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## General markdown" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Heading level 6 is not supported by Pandoc." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n\\n# Heading 1 \\n## Heading 2 \\n### Heading 3 \\n#### Heading 4 \\n##### Heading 5 \\n###### Heading 6');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\section{Heading 1}\n",
+       "\n",
+       "\\subsection{Heading 2}\n",
+       "\n",
+       "\\subsubsection{Heading 3}\n",
+       "\n",
+       "\\paragraph{Heading 4}\n",
+       "\n",
+       "\\subparagraph{Heading 5}\n",
+       "\n",
+       "Heading 6
NBViewer Output

Heading 1

\n", + "

Heading 2

\n", + "

Heading 3

\n", + "

Heading 4

\n", + "
Heading 5
\n", + "
Heading 6
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "\n", + "# Heading 1 \n", + "## Heading 2 \n", + "### Heading 3 \n", + "#### Heading 4 \n", + "##### Heading 5 \n", + "###### Heading 6\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Headers aren't recognized by (Pandoc on Windows?) if there isn't a blank line above the headers." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n# Heading 1 \\n## Heading 2 \\n### Heading 3 \\n#### Heading 4 \\n##### Heading 5 \\n###### Heading 6 ');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\section{Heading 1}\n",
+       "\n",
+       "\\subsection{Heading 2}\n",
+       "\n",
+       "\\subsubsection{Heading 3}\n",
+       "\n",
+       "\\paragraph{Heading 4}\n",
+       "\n",
+       "\\subparagraph{Heading 5}\n",
+       "\n",
+       "Heading 6
NBViewer Output

Heading 1

\n", + "

Heading 2

\n", + "

Heading 3

\n", + "

Heading 4

\n", + "
Heading 5
\n", + "
Heading 6
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "\n", - " * heading anchors\n", - " * note on remote images\n", "\n", - "06102013\n", "\n", - " * remove strip_math_space filter\n", - " * add lxml test\n", - " \n", - "" - ] - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "Utilities" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Define functions to render Markdown using the notebook and Pandoc." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "from IPython.nbconvert.utils.pandoc import pandoc\n", - "from IPython.display import HTML, Javascript, display\n", "\n", - "from IPython.nbconvert.filters import citation2latex, strip_files_prefix, \\\n", - " markdown2html, markdown2latex\n", "\n", - "def pandoc_render(markdown):\n", - " \"\"\"Render Pandoc Markdown->LaTeX content.\"\"\"\n", - " \n", - " ## Convert the markdown directly to latex. This is what nbconvert does.\n", - " #latex = pandoc(markdown, \"markdown\", \"latex\")\n", - " #html = pandoc(markdown, \"markdown\", \"html\", [\"--mathjax\"])\n", - " \n", - " # nbconvert template conversions\n", - " html = strip_files_prefix(markdown2html(markdown))\n", - " latex = markdown2latex(citation2latex(markdown))\n", - " display(HTML(data=\"
\" \\\n", - " \"
NBConvert Latex Output
\" \\\n", - " \"
\" + latex + \"
\"\\\n", - " \"
\" \\\n", - " \"
\" \\\n", - " \"
\" \\\n", - " \"
NBViewer Output
\" \\\n", - " \"
\" + html + \"
\" \\\n", - " \"
\"))\n", - " javascript = \"\"\"\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n", - "\"\"\"\n", - " display(Javascript(data=javascript))\n", "\n", - "def notebook_render(markdown):\n", - " javascript = \"\"\"\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\"\"\" + markdown.replace(\"\\\\\", \"\\\\\\\\\").replace(\"'\", \"\\'\").replace(\"\\n\", \"\\\\n\") + \"\"\"');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", "\n", - ");\n", - "container.show()\n", - "\"\"\"\n", - " display(Javascript(data=javascript))\n", "\n", - " \n", - "def pandoc_html_render(markdown):\n", - " \"\"\"Render Pandoc Markdown->LaTeX content.\"\"\"\n", - " \n", - " # Convert the markdown directly to latex. This is what nbconvert does.\n", - " latex = pandoc(markdown, \"markdown\", \"latex\")\n", - " \n", - " # Convert the pandoc generated latex to HTML so it can be rendered in \n", - " # the web browser.\n", - " html = pandoc(latex, \"latex\", \"html\", [\"--mathjax\"])\n", - " display(HTML(data=\"
HTML Pandoc Output
\" \\\n", - " \"
\" + html + \"
\"))\n", - " return html\n", - " \n", - "def compare_render(markdown):\n", - " notebook_render(markdown)\n", - " pandoc_render(markdown)" - ], - "language": "python", - "metadata": {}, - "outputs": [], - "prompt_number": 1 - }, - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Outputs" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "try:\n", - " import lxml\n", - " print 'LXML found!'\n", - "except:\n", - " print 'Warning! No LXML found - the old citation2latex filter will not work'" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "LXML found!\n" - ] - } - ], - "prompt_number": 1 - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "General markdown" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Heading level 6 is not supported by Pandoc." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", "\n", - "# Heading 1 \n", - "## Heading 2 \n", - "### Heading 3 \n", - "#### Heading 4 \n", - "##### Heading 5 \n", - "###### Heading 6\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n\\n# Heading 1 \\n## Heading 2 \\n### Heading 3 \\n#### Heading 4 \\n##### Heading 5 \\n###### Heading 6');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\section{Heading 1}\n",
-        "\n",
-        "\\subsection{Heading 2}\n",
-        "\n",
-        "\\subsubsection{Heading 3}\n",
-        "\n",
-        "\\paragraph{Heading 4}\n",
-        "\n",
-        "\\subparagraph{Heading 5}\n",
-        "\n",
-        "Heading 6
NBViewer Output

Heading 1

\n", - "

Heading 2

\n", - "

Heading 3

\n", - "

Heading 4

\n", - "
Heading 5
\n", - "
Heading 6
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 2 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Headers aren't recognized by (Pandoc on Windows?) if there isn't a blank line above the headers." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "# Heading 1 \n", - "## Heading 2 \n", - "### Heading 3 \n", - "#### Heading 4 \n", - "##### Heading 5 \n", - "###### Heading 6 \"\"\")\n", "\n", - "print(\"\\n\"*10)" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n# Heading 1 \\n## Heading 2 \\n### Heading 3 \\n#### Heading 4 \\n##### Heading 5 \\n###### Heading 6 ');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\section{Heading 1}\n",
-        "\n",
-        "\\subsection{Heading 2}\n",
-        "\n",
-        "\\subsubsection{Heading 3}\n",
-        "\n",
-        "\\paragraph{Heading 4}\n",
-        "\n",
-        "\\subparagraph{Heading 5}\n",
-        "\n",
-        "Heading 6
NBViewer Output

Heading 1

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Heading 2

\n", - "

Heading 3

\n", - "

Heading 4

\n", - "
Heading 5
\n", - "
Heading 6
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n" - ] - } - ], - "prompt_number": 3 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "If internal links are defined, these will not work in nbviewer and latex as the local link is not existing." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "[Link2Heading](http://127.0.0.1:8888/0a2d8086-ee24-4e5b-a32b-f66b525836cb#General-markdown)\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n[Link2Heading](http://127.0.0.1:8888/0a2d8086-ee24-4e5b-a32b-f66b525836cb#General-markdown)\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\href{http://127.0.0.1:8888/0a2d8086-ee24-4e5b-a32b-f66b525836cb\\#General-markdown}{Link2Heading}
NBViewer Output
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 4 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Basic Markdown bold and italic works." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "This is Markdown **bold** and *italic* text.\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\nThis is Markdown **bold** and *italic* text.\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
This is Markdown \\textbf{bold} and \\emph{italic} text.
NBViewer Output

This is Markdown bold and italic text.

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 5 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Nested lists work as well" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "- li 1\n", - "- li 2\n", - " 1. li 3\n", - " 1. li 4\n", - "- li 5\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n- li 1\\n- li 2\\n 1. li 3\\n 1. li 4\\n- li 5\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\begin{itemize}\n",
-        "\\itemsep1pt\\parskip0pt\\parsep0pt\n",
-        "\\item\n",
-        "  li 1\n",
-        "\\item\n",
-        "  li 2\n",
-        "\n",
-        "  \\begin{enumerate}\n",
-        "  \\def\\labelenumi{\\arabic{enumi}.}\n",
-        "  \\itemsep1pt\\parskip0pt\\parsep0pt\n",
-        "  \\item\n",
-        "    li 3\n",
-        "  \\item\n",
-        "    li 4\n",
-        "  \\end{enumerate}\n",
-        "\\item\n",
-        "  li 5\n",
-        "\\end{itemize}
NBViewer Output
    \n", - "
  • li 1
    • \n", - "
  • li 2\n", - "
      \n", - "
    1. li 3
      2. \n", - "
    2. li 4
      3. \n", - "
    • \n", - "
  • li 5
    • \n", - "
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 6 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Unicode support" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(ur\"\"\"\n", - "\u00fcberschu\u00df +***^\u00b0\u00b3\u00b3 \u03b1 \u03b2 \u03b8\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n\u00fcberschu\u00df +***^\u00b0\u00b3\u00b3 \u03b1 \u03b2 \u03b8\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\u00fcberschu\u00df +\\emph{*}\\^{}\u00b0\u00b3\u00b3 \u03b1 \u03b2 \u03b8
NBViewer Output

\u00fcberschu\u00df +*^\u00b0\u00b3\u00b3 \u03b1 \u03b2 \u03b8

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 7 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Pandoc may produce invalid latex, e.g \\sout is not allowed in headings" + "\n" ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "\n", - "# Heading 1 ~~strikeout~~\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n\\n# Heading 1 ~~strikeout~~\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\section{Heading 1 \\sout{strikeout}}
NBViewer Output

Heading 1 strikeout

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 8 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Horizontal lines work just fine" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "above\n", - "\n", - "--------\n", - "\n", - "below\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\nabove\\n\\n--------\\n\\nbelow\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
above\n",
-        "\n",
-        "\\begin{center}\\rule{3in}{0.4pt}\\end{center}\n",
-        "\n",
-        "below
NBViewer Output

above

\n", - "
\n", - "

below

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 9 - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "Extended markdown of pandoc" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "(maybe we should deactivate this) " - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "This is Markdown ~subscript~ and ^superscript^ text.\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\nThis is Markdown ~subscript~ and ^superscript^ text.\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
This is Markdown \\textsubscript{subscript} and\n",
-        "\\textsuperscript{superscript} text.
NBViewer Output

This is Markdown subscript and superscript text.

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 10 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "No space before underline behaves inconsistent (Pandoc extension: intraword_underscores - deactivate?)" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "This is Markdown not_italic_.\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\nThis is Markdown not_italic_.\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
This is Markdown not\\_italic\\_.
NBViewer Output

This is Markdown not_italic_.

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 11 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Pandoc allows to define tex macros which are respected for all output formats, the notebook not. " - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "\\newcommand{\\tuple}[1]{\\langle #1 \\rangle}\n", - "\n", - "$\\tuple{a, b, c}$\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n\\\\newcommand{\\\\tuple}[1]{\\\\langle #1 \\\\rangle}\\n\\n$\\\\tuple{a, b, c}$\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\newcommand{\\tuple}[1]{\\langle #1 \\rangle}\n",
-        "\n",
-        "$\\tuple{a, b, c}$
NBViewer Output

\\(\\langle a, b, c \\rangle\\)

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 12 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "When placing the \\newcommand inside a math environment it works within the notebook and nbviewer, but produces invalid latex (the newcommand is only valid in the same math environment)." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "$\\newcommand{\\foo}[1]{...:: #1 ::...}$\n", - "$\\foo{bar}$\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n$\\\\newcommand{\\\\foo}[1]{...:: #1 ::...}$\\n$\\\\foo{bar}$\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
$\\newcommand{\\foo}[1]{...:: #1 ::...}$ $\\foo{bar}$
NBViewer Output

\\(\\newcommand{\\foo}[1]{...:: #1 ::...}\\) \\(\\foo{bar}\\)

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 13 - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "HTML or LaTeX injections" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Raw HTML gets dropped entirely when converting to $\\LaTeX$." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "This is HTML bold and italic text.\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\nThis is HTML bold and italic text.\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
This is HTML bold and italic text.
NBViewer Output

This is HTML bold and italic text.

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 14 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Same for something like center" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "
Center aligned
\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n
Center aligned
\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
Center aligned
NBViewer Output
\n", - "Center aligned\n", - "
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 15 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Raw $\\LaTeX$ gets droppen entirely when converted to HTML. (I don't know why the HTML output is cropped here???)" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "This is \\LaTeX \\bf{bold} and \\emph{italic} text.\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\nThis is \\\\LaTeX \\\\bf{bold} and \\\\emph{italic} text.\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
This is \\LaTeX \\bf{bold} and \\emph{italic} text.
NBViewer Output

This is

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 16 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "A combination of raw $\\LaTeX$ and raw HTML" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "**foo** $\\left( \\sum_{k=1}^n a_k b_k \\right)^2 \\leq$ b\\$ar $$test$$ \n", - "\\cite{}\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n**foo** $\\\\left( \\\\sum_{k=1}^n a_k b_k \\\\right)^2 \\\\leq$ b\\\\$ar $$test$$ \\n\\\\cite{}\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\textbf{foo} $\\left( \\sum_{k=1}^n a_k b_k \\right)^2 \\leq$ b\\$ar \\[test\\]\n",
-        "\\cite{}
NBViewer Output

foo \\(\\left( \\sum_{k=1}^n a_k b_k \\right)^2 \\leq\\) b$ar \\[test\\]

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 17 - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "Tables" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "HTML tables render in the notebook, but not in Pandoc." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
ab
cd
\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n\\n \\n \\n \\n \\n \\n \\n \\n \\n
ab
cd
\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
a\n",
-        "\n",
-        "b\n",
-        "\n",
-        "c\n",
-        "\n",
-        "d
NBViewer Output
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "a\n", - "\n", - "b\n", - "
\n", - "c\n", - "\n", - "d\n", - "
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 18 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Instead, Pandoc supports simple ascii tables. Unfortunately marked.js doesn't support this, and therefore it is not supported in the notebook." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "+---+---+\n", - "| a | b |\n", - "+---+---+\n", - "| c | d |\n", - "+---+---+\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n+---+---+\\n| a | b |\\n+---+---+\\n| c | d |\\n+---+---+\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\begin{longtable}[c]{@{}ll@{}}\n",
-        "\\hline\\noalign{\\medskip}\n",
-        "\\begin{minipage}[t]{0.06\\columnwidth}\\raggedright\n",
-        "a\n",
-        "\\end{minipage} & \\begin{minipage}[t]{0.06\\columnwidth}\\raggedright\n",
-        "b\n",
-        "\\end{minipage}\n",
-        "\\\\\\noalign{\\medskip}\n",
-        "\\begin{minipage}[t]{0.06\\columnwidth}\\raggedright\n",
-        "c\n",
-        "\\end{minipage} & \\begin{minipage}[t]{0.06\\columnwidth}\\raggedright\n",
-        "d\n",
-        "\\end{minipage}\n",
-        "\\\\\\noalign{\\medskip}\n",
-        "\\hline\n",
-        "\\end{longtable}
NBViewer Output
\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "

a

b

c

d

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 19 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "An alternative to basic ascii tables is pipe tables. Pipe tables can be recognized by Pandoc and are supported by marked, hence, this is the **best way to add tables**." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "|Left |Center |Right|\n", - "|:----|:-----:|----:|\n", - "|Text1|Text2 |Text3|\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n|Left |Center |Right|\\n|:----|:-----:|----:|\\n|Text1|Text2 |Text3|\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\begin{longtable}[c]{@{}lcr@{}}\n",
-        "\\hline\\noalign{\\medskip}\n",
-        "Left & Center & Right\n",
-        "\\\\\\noalign{\\medskip}\n",
-        "\\hline\\noalign{\\medskip}\n",
-        "Text1 & Text2 & Text3\n",
-        "\\\\\\noalign{\\medskip}\n",
-        "\\hline\n",
-        "\\end{longtable}
NBViewer Output
\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
LeftCenterRight
Text1Text2Text3
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 20 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Pandoc recognizes cell alignment in simple tables. Since marked.js doesn't recognize ascii tables, it can't render this table." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "Right Aligned Center Aligned Left Aligned\n", - "------------- -------------- ------------\n", - " Why does this\n", - " actually work? Who\n", - " knows ...\n", - "\"\"\")\n", - "\n", - "print(\"\\n\"*5)" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\nRight Aligned Center Aligned Left Aligned\\n------------- -------------- ------------\\n Why does this\\n actually work? Who\\n knows ...\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\begin{longtable}[c]{@{}lll@{}}\n",
-        "\\hline\\noalign{\\medskip}\n",
-        "Right Aligned & Center Aligned & Left Aligned\n",
-        "\\\\\\noalign{\\medskip}\n",
-        "\\hline\\noalign{\\medskip}\n",
-        "Why & does & this\n",
-        "\\\\\\noalign{\\medskip}\n",
-        "actually & work? & Who\n",
-        "\\\\\\noalign{\\medskip}\n",
-        "knows & \\ldots{} &\n",
-        "\\\\\\noalign{\\medskip}\n",
-        "\\hline\n",
-        "\\end{longtable}
NBViewer Output
\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
Right AlignedCenter AlignedLeft Aligned
Whydoesthis
actuallywork?Who
knows...
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n" - ] - } - ], - "prompt_number": 21 - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "Images" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Markdown images work on both. However, remote images are not allowed in $\\LaTeX$. Maybe add a preprocessor to download these.\n", - "The alternate text is displayed in nbviewer next to the image." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "![Alternate Text](http://ipython.org/_static/IPy_header.png)\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n![Alternate Text](http://ipython.org/_static/IPy_header.png)\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\begin{figure}[htbp]\n",
-        "\\centering\n",
-        "\\includegraphics{http://ipython.org/_static/IPy_header.png}\n",
-        "\\caption{Alternate Text}\n",
-        "\\end{figure}
NBViewer Output
\n", - "\"Alternate

Alternate Text

\n", - "
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 22 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "HTML Images only work in the notebook." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
NBViewer Output

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 23 - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "Math" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Simple inline and displaystyle maths work fine" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "My equation:\n", - "$$ 5/x=2y $$\n", - "\n", - "It is inline $ 5/x=2y $ here.\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\nMy equation:\\n$$ 5/x=2y $$\\n\\nIt is inline $ 5/x=2y $ here.\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
My equation: \\[ 5/x=2y \\]\n",
-        "\n",
-        "It is inline \\$ 5/x=2y \\$ here.
NBViewer Output

My equation: \\[ 5/x=2y \\]

\n", - "

It is inline $ 5/x=2y $ here.

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 24 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "If the first \\$ is on a new line, the equation is not captured by md2tex, if both \\$s are on a new line md2html fails (Note the raw latex is dropped) but the notebook renders it correctly." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "$5 \\cdot x=2$\n", - "\n", - "$\n", - "5 \\cdot x=2$\n", + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "# Heading 1 \n", + "## Heading 2 \n", + "### Heading 3 \n", + "#### Heading 4 \n", + "##### Heading 5 \n", + "###### Heading 6 \"\"\")\n", + "\n", + "print(\"\\n\"*10)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If internal links are defined, these will not work in nbviewer and latex as the local link is not existing." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n[Link2Heading](http://127.0.0.1:8888/0a2d8086-ee24-4e5b-a32b-f66b525836cb#General-markdown)\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\href{http://127.0.0.1:8888/0a2d8086-ee24-4e5b-a32b-f66b525836cb\\#General-markdown}{Link2Heading}
NBViewer Output
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "[Link2Heading](http://127.0.0.1:8888/0a2d8086-ee24-4e5b-a32b-f66b525836cb#General-markdown)\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Basic Markdown bold and italic works." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nThis is Markdown **bold** and *italic* text.\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
This is Markdown \\textbf{bold} and \\emph{italic} text.
NBViewer Output

This is Markdown bold and italic text.

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "This is Markdown **bold** and *italic* text.\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Nested lists work as well" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n- li 1\\n- li 2\\n 1. li 3\\n 1. li 4\\n- li 5\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\begin{itemize}\n",
+       "\\itemsep1pt\\parskip0pt\\parsep0pt\n",
+       "\\item\n",
+       "  li 1\n",
+       "\\item\n",
+       "  li 2\n",
+       "\n",
+       "  \\begin{enumerate}\n",
+       "  \\def\\labelenumi{\\arabic{enumi}.}\n",
+       "  \\itemsep1pt\\parskip0pt\\parsep0pt\n",
+       "  \\item\n",
+       "    li 3\n",
+       "  \\item\n",
+       "    li 4\n",
+       "  \\end{enumerate}\n",
+       "\\item\n",
+       "  li 5\n",
+       "\\end{itemize}
NBViewer Output
    \n", + "
  • li 1
    • \n", + "
  • li 2\n", + "
      \n", + "
    1. li 3
      2. \n", + "
    2. li 4
      3. \n", + "
    • \n", + "
  • li 5
    • \n", + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "- li 1\n", + "- li 2\n", + " 1. li 3\n", + " 1. li 4\n", + "- li 5\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Unicode support" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nüberschuß +***^°³³ α β θ\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
überschuß +\\emph{*}\\^{}°³³ α β θ
NBViewer Output

überschuß +*^°³³ α β θ

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(ur\"\"\"\n", + "überschuß +***^°³³ α β θ\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pandoc may produce invalid latex, e.g \\sout is not allowed in headings" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n\\n# Heading 1 ~~strikeout~~\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\section{Heading 1 \\sout{strikeout}}
NBViewer Output

Heading 1 strikeout

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "\n", + "# Heading 1 ~~strikeout~~\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Horizontal lines work just fine" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nabove\\n\\n--------\\n\\nbelow\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
above\n",
+       "\n",
+       "\\begin{center}\\rule{3in}{0.4pt}\\end{center}\n",
+       "\n",
+       "below
NBViewer Output

above

\n", + "
\n", + "

below

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "above\n", + "\n", + "--------\n", + "\n", + "below\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Extended markdown of pandoc" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "(maybe we should deactivate this) " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nThis is Markdown ~subscript~ and ^superscript^ text.\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
This is Markdown \\textsubscript{subscript} and\n",
+       "\\textsuperscript{superscript} text.
NBViewer Output

This is Markdown subscript and superscript text.

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "This is Markdown ~subscript~ and ^superscript^ text.\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "No space before underline behaves inconsistent (Pandoc extension: intraword_underscores - deactivate?)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nThis is Markdown not_italic_.\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
This is Markdown not\\_italic\\_.
NBViewer Output

This is Markdown not_italic_.

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "This is Markdown not_italic_.\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pandoc allows to define tex macros which are respected for all output formats, the notebook not. " + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n\\\\newcommand{\\\\tuple}[1]{\\\\langle #1 \\\\rangle}\\n\\n$\\\\tuple{a, b, c}$\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\newcommand{\\tuple}[1]{\\langle #1 \\rangle}\n",
+       "\n",
+       "$\\tuple{a, b, c}$
NBViewer Output

\\(\\langle a, b, c \\rangle\\)

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "\\newcommand{\\tuple}[1]{\\langle #1 \\rangle}\n", + "\n", + "$\\tuple{a, b, c}$\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "When placing the \\newcommand inside a math environment it works within the notebook and nbviewer, but produces invalid latex (the newcommand is only valid in the same math environment)." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n$\\\\newcommand{\\\\foo}[1]{...:: #1 ::...}$\\n$\\\\foo{bar}$\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
$\\newcommand{\\foo}[1]{...:: #1 ::...}$ $\\foo{bar}$
NBViewer Output

\\(\\newcommand{\\foo}[1]{...:: #1 ::...}\\) \\(\\foo{bar}\\)

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "$\\newcommand{\\foo}[1]{...:: #1 ::...}$\n", + "$\\foo{bar}$\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## HTML or LaTeX injections" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Raw HTML gets dropped entirely when converting to $\\LaTeX$." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nThis is HTML bold and italic text.\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
This is HTML bold and italic text.
NBViewer Output

This is HTML bold and italic text.

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "This is HTML bold and italic text.\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Same for something like center" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n
Center aligned
\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
Center aligned
NBViewer Output
\n", + "Center aligned\n", + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "
Center aligned
\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Raw $\\LaTeX$ gets droppen entirely when converted to HTML. (I don't know why the HTML output is cropped here???)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nThis is \\\\LaTeX \\\\bf{bold} and \\\\emph{italic} text.\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
This is \\LaTeX \\bf{bold} and \\emph{italic} text.
NBViewer Output

This is

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "This is \\LaTeX \\bf{bold} and \\emph{italic} text.\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A combination of raw $\\LaTeX$ and raw HTML" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n**foo** $\\\\left( \\\\sum_{k=1}^n a_k b_k \\\\right)^2 \\\\leq$ b\\\\$ar $$test$$ \\n\\\\cite{}\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\textbf{foo} $\\left( \\sum_{k=1}^n a_k b_k \\right)^2 \\leq$ b\\$ar \\[test\\]\n",
+       "\\cite{}
NBViewer Output

foo \\(\\left( \\sum_{k=1}^n a_k b_k \\right)^2 \\leq\\) b$ar \\[test\\]

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "**foo** $\\left( \\sum_{k=1}^n a_k b_k \\right)^2 \\leq$ b\\$ar $$test$$ \n", + "\\cite{}\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Tables" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "HTML tables render in the notebook, but not in Pandoc." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n\\n \\n \\n \\n \\n \\n \\n \\n \\n
ab
cd
\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
a\n",
+       "\n",
+       "b\n",
+       "\n",
+       "c\n",
+       "\n",
+       "d
NBViewer Output
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "a\n", + "\n", + "b\n", + "
\n", + "c\n", + "\n", + "d\n", + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
ab
cd
\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Instead, Pandoc supports simple ascii tables. Unfortunately marked.js doesn't support this, and therefore it is not supported in the notebook." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n+---+---+\\n| a | b |\\n+---+---+\\n| c | d |\\n+---+---+\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\begin{longtable}[c]{@{}ll@{}}\n",
+       "\\hline\\noalign{\\medskip}\n",
+       "\\begin{minipage}[t]{0.06\\columnwidth}\\raggedright\n",
+       "a\n",
+       "\\end{minipage} & \\begin{minipage}[t]{0.06\\columnwidth}\\raggedright\n",
+       "b\n",
+       "\\end{minipage}\n",
+       "\\\\\\noalign{\\medskip}\n",
+       "\\begin{minipage}[t]{0.06\\columnwidth}\\raggedright\n",
+       "c\n",
+       "\\end{minipage} & \\begin{minipage}[t]{0.06\\columnwidth}\\raggedright\n",
+       "d\n",
+       "\\end{minipage}\n",
+       "\\\\\\noalign{\\medskip}\n",
+       "\\hline\n",
+       "\\end{longtable}
NBViewer Output
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "

a

b

c

d

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "+---+---+\n", + "| a | b |\n", + "+---+---+\n", + "| c | d |\n", + "+---+---+\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "An alternative to basic ascii tables is pipe tables. Pipe tables can be recognized by Pandoc and are supported by marked, hence, this is the **best way to add tables**." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n|Left |Center |Right|\\n|:----|:-----:|----:|\\n|Text1|Text2 |Text3|\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\begin{longtable}[c]{@{}lcr@{}}\n",
+       "\\hline\\noalign{\\medskip}\n",
+       "Left & Center & Right\n",
+       "\\\\\\noalign{\\medskip}\n",
+       "\\hline\\noalign{\\medskip}\n",
+       "Text1 & Text2 & Text3\n",
+       "\\\\\\noalign{\\medskip}\n",
+       "\\hline\n",
+       "\\end{longtable}
NBViewer Output
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
LeftCenterRight
Text1Text2Text3
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "|Left |Center |Right|\n", + "|:----|:-----:|----:|\n", + "|Text1|Text2 |Text3|\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pandoc recognizes cell alignment in simple tables. Since marked.js doesn't recognize ascii tables, it can't render this table." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nRight Aligned Center Aligned Left Aligned\\n------------- -------------- ------------\\n Why does this\\n actually work? Who\\n knows ...\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\begin{longtable}[c]{@{}lll@{}}\n",
+       "\\hline\\noalign{\\medskip}\n",
+       "Right Aligned & Center Aligned & Left Aligned\n",
+       "\\\\\\noalign{\\medskip}\n",
+       "\\hline\\noalign{\\medskip}\n",
+       "Why & does & this\n",
+       "\\\\\\noalign{\\medskip}\n",
+       "actually & work? & Who\n",
+       "\\\\\\noalign{\\medskip}\n",
+       "knows & \\ldots{} &\n",
+       "\\\\\\noalign{\\medskip}\n",
+       "\\hline\n",
+       "\\end{longtable}
NBViewer Output
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
Right AlignedCenter AlignedLeft Aligned
Whydoesthis
actuallywork?Who
knows...
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "\n", - "$\n", - "5 \\cdot x=2\n", - "$\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n$5 \\\\cdot x=2$\\n\\n$\\n5 \\\\cdot x=2$\\n\\n$\\n5 \\\\cdot x=2\\n$\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
$5 \\cdot x=2$\n",
-        "\n",
-        "\\$ 5 \\cdot x=2\\$\n",
-        "\n",
-        "\\$ 5 \\cdot x=2 \\$
NBViewer Output

\\(5 \\cdot x=2\\)

\n", - "

$ 5 x=2$

\n", - "

$ 5 x=2 $

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 25 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "MathJax permits some $\\LaTeX$ math constructs without \\$s, of course these raw $\\LaTeX$ is stripped when converting to html.\n", - "Moreove, the & are escaped by the lxml parsing [#4251](https://github.com/ipython/ipython/issues/4251)." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "\\begin{align}\n", - "a & b\\\\\n", - "d & c\n", - "\\end{align}\n", "\n", - "\\begin{eqnarray}\n", - "a & b \\\\\n", - "c & d\n", - "\\end{eqnarray}\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n\\\\begin{align}\\na & b\\\\\\\\\\nd & c\\n\\\\end{align}\\n\\n\\\\begin{eqnarray}\\na & b \\\\\\\\\\nc & d\\n\\\\end{eqnarray}\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
\\begin{align}\n",
-        "a & b\\\\\n",
-        "d & c\n",
-        "\\end{align}\n",
-        "\n",
-        "\\begin{eqnarray}\n",
-        "a & b \\\\\n",
-        "c & d\n",
-        "\\end{eqnarray}
NBViewer Output
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 26 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "There is another lxml issue, [#4283](https://github.com/ipython/ipython/issues/4283)" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "1<2 is true, but 3>4 is false.\n", "\n", - "$1<2$ is true, but $3>4$ is false.\n", "\n", - "1<2 it is even worse if it is alone in a line.\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\n1<2 is true, but 3>4 is false.\\n\\n$1<2$ is true, but $3>4$ is false.\\n\\n1<2 it is even worse if it is alone in a line.\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
14 is false.\n",
-        "\n",
-        "$14$ is false.\n",
-        "\n",
-        "1
NBViewer Output

1<2 is true, but 3>4 is false.

\n", - "

\\(1<2\\) is true, but \\(3>4\\) is false.

\n", - "

1<2 it is even worse if it is alone in a line.

" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 27 - }, - { - "cell_type": "heading", - "level": 2, - "metadata": {}, - "source": [ - "Listings, and Code blocks" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "some source code\n", "\n", - "```\n", - "a = \"test\"\n", - "print(a)\n", - "```\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\nsome source code\\n\\n```\\na = \"test\"\\nprint(a)\\n```\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
some source code\n",
-        "\n",
-        "\\begin{verbatim}\n",
-        "a = \"test\"\n",
-        "print(a)\n",
-        "\\end{verbatim}
NBViewer Output

some source code

\n", - "
a = "test"\n",
-        "print(a)
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 28 - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Language specific syntax highlighting by Pandoc requires additional dependencies to render correctly." + "\n" ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "compare_render(r\"\"\"\n", - "some source code\n", - "\n", - "```python\n", - "a = \"test\"\n", - "print(a)\n", - "```\n", - "\"\"\")" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "javascript": [ - "\n", - "var mdcell = new IPython.MarkdownCell();\n", - "mdcell.create_element();\n", - "mdcell.set_text('\\nsome source code\\n\\n```python\\na = \"test\"\\nprint(a)\\n```\\n');\n", - "mdcell.render();\n", - "$(element).append(mdcell.element)\n", - ".removeClass()\n", - ".css('left', '66%')\n", - ".css('position', 'absolute')\n", - ".css('width', '30%')\n", - "mdcell.element.prepend(\n", - " $('
')\n", - " .removeClass()\n", - " .css('background', '#AAAAFF')\n", - " .css('width', '100 %')\n", - " .html('Notebook Output')\n", - "\n", - ");\n", - "container.show()\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "html": [ - "
NBConvert Latex Output
some source code\n",
-        "\n",
-        "\\begin{Shaded}\n",
-        "\\begin{Highlighting}[]\n",
-        "\\NormalTok{a = }\\StringTok{\"test\"}\n",
-        "\\KeywordTok{print}\\NormalTok{(a)}\n",
-        "\\end{Highlighting}\n",
-        "\\end{Shaded}
NBViewer Output

some source code

\n", - "
a = "test"\n",
-        "print(a)
" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - }, - { - "javascript": [ - "\n", - " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" - ], - "metadata": {}, - "output_type": "display_data", - "text": [ - "" - ] - } - ], - "prompt_number": 29 } ], - "metadata": {} + "source": [ + "compare_render(r\"\"\"\n", + "Right Aligned Center Aligned Left Aligned\n", + "------------- -------------- ------------\n", + " Why does this\n", + " actually work? Who\n", + " knows ...\n", + "\"\"\")\n", + "\n", + "print(\"\\n\"*5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Images" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Markdown images work on both. However, remote images are not allowed in $\\LaTeX$. Maybe add a preprocessor to download these.\n", + "The alternate text is displayed in nbviewer next to the image." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n![Alternate Text](http://ipython.org/_static/IPy_header.png)\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\begin{figure}[htbp]\n",
+       "\\centering\n",
+       "\\includegraphics{http://ipython.org/_static/IPy_header.png}\n",
+       "\\caption{Alternate Text}\n",
+       "\\end{figure}
NBViewer Output
\n", + "\"Alternate

Alternate Text

\n", + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "![Alternate Text](http://ipython.org/_static/IPy_header.png)\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "HTML Images only work in the notebook." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
NBViewer Output

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Math" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Simple inline and displaystyle maths work fine" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nMy equation:\\n$$ 5/x=2y $$\\n\\nIt is inline $ 5/x=2y $ here.\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
My equation: \\[ 5/x=2y \\]\n",
+       "\n",
+       "It is inline \\$ 5/x=2y \\$ here.
NBViewer Output

My equation: \\[ 5/x=2y \\]

\n", + "

It is inline $ 5/x=2y $ here.

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "My equation:\n", + "$$ 5/x=2y $$\n", + "\n", + "It is inline $ 5/x=2y $ here.\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If the first \\$ is on a new line, the equation is not captured by md2tex, if both \\$s are on a new line md2html fails (Note the raw latex is dropped) but the notebook renders it correctly." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n$5 \\\\cdot x=2$\\n\\n$\\n5 \\\\cdot x=2$\\n\\n$\\n5 \\\\cdot x=2\\n$\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
$5 \\cdot x=2$\n",
+       "\n",
+       "\\$ 5 \\cdot x=2\\$\n",
+       "\n",
+       "\\$ 5 \\cdot x=2 \\$
NBViewer Output

\\(5 \\cdot x=2\\)

\n", + "

$ 5 x=2$

\n", + "

$ 5 x=2 $

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "$5 \\cdot x=2$\n", + "\n", + "$\n", + "5 \\cdot x=2$\n", + "\n", + "$\n", + "5 \\cdot x=2\n", + "$\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "MathJax permits some $\\LaTeX$ math constructs without \\$s, of course these raw $\\LaTeX$ is stripped when converting to html.\n", + "Moreove, the & are escaped by the lxml parsing [#4251](https://github.com/ipython/ipython/issues/4251)." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n\\\\begin{align}\\na & b\\\\\\\\\\nd & c\\n\\\\end{align}\\n\\n\\\\begin{eqnarray}\\na & b \\\\\\\\\\nc & d\\n\\\\end{eqnarray}\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
\\begin{align}\n",
+       "a &amp; b\\\\\n",
+       "d &amp; c\n",
+       "\\end{align}\n",
+       "\n",
+       "\\begin{eqnarray}\n",
+       "a &amp; b \\\\\n",
+       "c &amp; d\n",
+       "\\end{eqnarray}
NBViewer Output
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "\\begin{align}\n", + "a & b\\\\\n", + "d & c\n", + "\\end{align}\n", + "\n", + "\\begin{eqnarray}\n", + "a & b \\\\\n", + "c & d\n", + "\\end{eqnarray}\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "There is another lxml issue, [#4283](https://github.com/ipython/ipython/issues/4283)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\n1<2 is true, but 3>4 is false.\\n\\n$1<2$ is true, but $3>4$ is false.\\n\\n1<2 it is even worse if it is alone in a line.\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
14 is false.\n",
+       "\n",
+       "$14$ is false.\n",
+       "\n",
+       "1
NBViewer Output

1<2 is true, but 3>4 is false.

\n", + "

\\(1<2\\) is true, but \\(3>4\\) is false.

\n", + "

1<2 it is even worse if it is alone in a line.

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "1<2 is true, but 3>4 is false.\n", + "\n", + "$1<2$ is true, but $3>4$ is false.\n", + "\n", + "1<2 it is even worse if it is alone in a line.\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Listings, and Code blocks" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nsome source code\\n\\n```\\na = \"test\"\\nprint(a)\\n```\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
some source code\n",
+       "\n",
+       "\\begin{verbatim}\n",
+       "a = \"test\"\n",
+       "print(a)\n",
+       "\\end{verbatim}
NBViewer Output

some source code

\n", + "
a = "test"\n",
+       "print(a)
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "some source code\n", + "\n", + "```\n", + "a = \"test\"\n", + "print(a)\n", + "```\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Language specific syntax highlighting by Pandoc requires additional dependencies to render correctly." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "application/javascript": [ + "\n", + "var mdcell = new IPython.MarkdownCell();\n", + "mdcell.create_element();\n", + "mdcell.set_text('\\nsome source code\\n\\n```python\\na = \"test\"\\nprint(a)\\n```\\n');\n", + "mdcell.render();\n", + "$(element).append(mdcell.element)\n", + ".removeClass()\n", + ".css('left', '66%')\n", + ".css('position', 'absolute')\n", + ".css('width', '30%')\n", + "mdcell.element.prepend(\n", + " $('
')\n", + " .removeClass()\n", + " .css('background', '#AAAAFF')\n", + " .css('width', '100 %')\n", + " .html('Notebook Output')\n", + "\n", + ");\n", + "container.show()\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
NBConvert Latex Output
some source code\n",
+       "\n",
+       "\\begin{Shaded}\n",
+       "\\begin{Highlighting}[]\n",
+       "\\NormalTok{a = }\\StringTok{\"test\"}\n",
+       "\\KeywordTok{print}\\NormalTok{(a)}\n",
+       "\\end{Highlighting}\n",
+       "\\end{Shaded}
NBViewer Output

some source code

\n", + "
a = "test"\n",
+       "print(a)
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + " $.getScript(\"https://google-code-prettify.googlecode.com/svn/loader/run_prettify.js\");\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "compare_render(r\"\"\"\n", + "some source code\n", + "\n", + "```python\n", + "a = \"test\"\n", + "print(a)\n", + "```\n", + "\"\"\")" + ] } - ] -} \ No newline at end of file + ], + "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": "3.4.2" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/tools/tests/Test Output Callbacks.ipynb b/tools/tests/Test Output Callbacks.ipynb index 528bcdc..94ec190 100644 --- a/tools/tests/Test Output Callbacks.ipynb +++ b/tools/tests/Test Output Callbacks.ipynb @@ -1,269 +1,291 @@ { - "metadata": { - "name": "" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Basic Output" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "from IPython.display import display" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "print('hi')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "display('hi')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "plt.plot([1,3,2])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%%javascript\n", + "console.log(\"I ran!\");" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%%html\n", + "bold" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%%latex\n", + "$$\n", + "a = 5\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# input_request" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "raw_input(\"prompt > \")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# set_next_input" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%%writefile tst.py\n", + "def foo():\n", + " pass\n" + ] + }, { - "cells": [ - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Basic Output" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "from IPython.display import display" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "print('hi')" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "display('hi')" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "1" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", - "plt.plot([1,3,2])" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "%%javascript\n", - "console.log(\"I ran!\");" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "%%html\n", - "bold" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "%%latex\n", - "$$\n", - "a = 5\n", - "$$" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "input_request" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "raw_input(\"prompt > \")" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "set_next_input" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "%%writefile tst.py\n", - "def foo():\n", - " pass\n" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "%load tst.py" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "Pager in execute_reply" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "plt?" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "object_info" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "# press shift-tab after parentheses\n", - "int(" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "complete" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "# press tab after f\n", - "f" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "heading", - "level": 1, - "metadata": {}, - "source": [ - "clear_output" - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "import sys, time\n", - "from IPython.display import clear_output" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "for i in range(10):\n", - " clear_output()\n", - " time.sleep(0.25)\n", - " print(i)\n", - " sys.stdout.flush()\n", - " time.sleep(0.25)\n" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "for i in range(10):\n", - " clear_output(wait=True)\n", - " time.sleep(0.25)\n", - " print(i)\n", - " sys.stdout.flush()\n" - ], - "language": "python", - "metadata": {}, - "outputs": [] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [], - "language": "python", - "metadata": {}, - "outputs": [] - } - ], - "metadata": {} + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%load tst.py" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Pager in execute_reply" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "plt?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# object_info" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# press shift-tab after parentheses\n", + "int(" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# complete" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# press tab after f\n", + "f" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# clear_output" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import sys, time\n", + "from IPython.display import clear_output" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "for i in range(10):\n", + " clear_output()\n", + " time.sleep(0.25)\n", + " print(i)\n", + " sys.stdout.flush()\n", + " time.sleep(0.25)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "for i in range(10):\n", + " clear_output(wait=True)\n", + " time.sleep(0.25)\n", + " print(i)\n", + " sys.stdout.flush()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] } - ] -} \ No newline at end of file + ], + "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": "3.4.2" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/tools/tests/heartbeat/gilsleep.ipynb b/tools/tests/heartbeat/gilsleep.ipynb index a9b3d06..026682f 100644 --- a/tools/tests/heartbeat/gilsleep.ipynb +++ b/tools/tests/heartbeat/gilsleep.ipynb @@ -1,61 +1,72 @@ { - "metadata": { - "name": "gilsleep" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Holding the GIL for too long could disrupt the heartbeat due to non-copying sends.\n", + "\n", + "The following cell repeatedly calls a function that holds the GIL for five seconds.\n", + "\n", + "The heartbeat will fail after a few iterations prior to fixing Issue [#1260](https://github.com/ipython/ipython/issues/1260)." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import sys\n", + "import time\n", + "\n", + "from cython import inline\n", + "\n", + "def gilsleep(t):\n", + " \"\"\"gil-holding sleep with cython.inline\"\"\"\n", + " code = '\\n'.join([\n", + " 'from posix cimport unistd',\n", + " 'unistd.sleep(t)',\n", + " ])\n", + " while True:\n", + " inline(code, quiet=True, t=t)\n", + " print time.time()\n", + " sys.stdout.flush() # this is important\n", + "\n", + "gilsleep(5)" + ] + }, { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Holding the GIL for too long could disrupt the heartbeat due to non-copying sends.\n", - "\n", - "The following cell repeatedly calls a function that holds the GIL for five seconds.\n", - "\n", - "The heartbeat will fail after a few iterations prior to fixing Issue [#1260](https://github.com/ipython/ipython/issues/1260)." - ] - }, - { - "cell_type": "code", - "collapsed": false, - "input": [ - "import sys\n", - "import time\n", - "\n", - "from cython import inline\n", - "\n", - "def gilsleep(t):\n", - " \"\"\"gil-holding sleep with cython.inline\"\"\"\n", - " code = '\\n'.join([\n", - " 'from posix cimport unistd',\n", - " 'unistd.sleep(t)',\n", - " ])\n", - " while True:\n", - " inline(code, quiet=True, t=t)\n", - " print time.time()\n", - " sys.stdout.flush() # this is important\n", - "\n", - "gilsleep(5)" - ], - "language": "python", - "metadata": {}, - "outputs": [], - "prompt_number": 1 - }, - { - "cell_type": "code", - "collapsed": true, - "input": [], - "language": "python", - "metadata": {}, - "outputs": [], - "prompt_number": null - } - ], - "metadata": {} + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] } - ] -} \ No newline at end of file + ], + "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": "3.4.2" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/tools/tests/mpl-switch/Matplotlib Switching.ipynb b/tools/tests/mpl-switch/Matplotlib Switching.ipynb index bb6e5ff..252fe67 100644 --- a/tools/tests/mpl-switch/Matplotlib Switching.ipynb +++ b/tools/tests/mpl-switch/Matplotlib Switching.ipynb @@ -1,102 +1,654 @@ { - "metadata": { - "name": "", - "signature": "sha256:16dbf1191870d235be65800e4146b76c77118bb66575109c250a0cbce0e8e1ac" - }, - "nbformat": 3, - "nbformat_minor": 0, - "worksheets": [ + "cells": [ { - "cells": [ + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ { - "cell_type": "code", - "collapsed": false, - "input": [ - "# Should pop up a GUI window\n", - "%matplotlib\n", - "import matplotlib.pyplot as plt\n", - "plt.plot([1,2,3])" - ], - "language": "python", - "metadata": {}, - "outputs": [ - { - "output_type": "stream", - "stream": "stdout", - "text": [ - "Using matplotlib backend: MacOSX\n" - ] - }, - { - "metadata": {}, - "output_type": "pyout", - "prompt_number": 1, - "text": [ - "[]" - ] - } - ], - "prompt_number": 1 + "name": "stdout", + "output_type": "stream", + "text": [ + "Using matplotlib backend: MacOSX\n" + ] }, { - "cell_type": "code", - "collapsed": false, - "input": [ - "# Should make an inline figure\n", - "%matplotlib inline\n", - "plt.plot([1,2,3])" - ], - "language": "python", + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 1, "metadata": {}, - "outputs": [ - { - "metadata": {}, - "output_type": "pyout", - "prompt_number": 2, - "text": [ - "[]" - ] - }, - { - "metadata": { - "png": { - "height": 379, - "width": 600 - } - }, - "output_type": "display_data", - "png": 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xs6mZlr5RAN532QK+sL6O0jxPnpE080zqlSmZTGaA//ImXw8SicTdnIpYaybz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\nJtIBRTkxbllby4eurCDqpYOSJEmSJM0bRizNWEfbB9nR3MKJvjEA3ru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- "text": [ - "" - ] - } - ], - "prompt_number": 2 - }, + "output_type": "execute_result" + } + ], + "source": [ + "# Should pop up a GUI window\n", + "%matplotlib\n", + "import matplotlib.pyplot as plt\n", + "plt.plot([1,2,3])" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ { - "cell_type": "code", - "collapsed": false, - "input": [ - "# New GUI window--should *NOT* have the visual settings of inline\n", - "%matplotlib qt\n", - "plt.plot([1,2,3])" - ], - "language": "python", + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 2, "metadata": {}, - "outputs": [ - { - "metadata": {}, - "output_type": "pyout", - "prompt_number": 3, - "text": [ - "[]" - ] + "output_type": "execute_result" + }, + { + "data": { + "image/png": [ + "iVBORw0KGgoAAAANSUhEUgAABLEAAAL3CAYAAAB1btcfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\n", + "AAAWJQAAFiUBSVIk8AAAIABJREFUeJzs3Wl0nPWB5/tvVWnfZVmytrLZDcbYeLcld2cjnSYhO5WN\n", + 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"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": "3.4.2" } - ] -} \ No newline at end of file + }, + "nbformat": 4, + "nbformat_minor": 0 +}