diff --git a/CHANGELOG.md b/CHANGELOG.md index 384e5255..31ad49c0 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,16 @@ # Changelog +## 1.6.4 (July 20, 2023) + +### New features +- Optimized/vectorized point rotation, speeding up the `rotate()` operation by as much as 150x(!) (thanks Bas Nijholt @basnijholt) +- Added proper `pg.fill_rectangle()` [examples and documentation](https://phidl.readthedocs.io/en/latest/geometry_reference.html#Fill-tool) + +### Bugfixes +- Fixed `pg.grid()` to allow for empty `shape` parameter (thanks Samuel Gyger @gyger) +- Allow `pg.grid()` spacing to be a single integer (thanks Samuel Gyger @gyger) +- Fix to np.bool + ## 1.6.3 (Feb 9, 2023) diff --git a/README.md b/README.md index 474bbe8a..207ed924 100644 --- a/README.md +++ b/README.md @@ -7,7 +7,8 @@ GDS scripting for Python that's intuitive, fast, and powerful. - [**Installation / requirements**](#installation--requirements) - [**Tutorial + examples**](https://phidl.readthedocs.io/en/latest/tutorials.html) (or [try an interactive notebook](https://mybinder.org/v2/gh/amccaugh/phidl/master?filepath=phidl_tutorial_example.ipynb)) - [**Geometry library + function documentation**](https://phidl.readthedocs.io/en/latest/geometry_reference.html) -- [Changelog](https://github.com/amccaugh/phidl/blob/master/CHANGELOG.md) (latest update 1.6.3 on Feb 9, 2023) +- [Changelog](https://github.com/amccaugh/phidl/blob/master/CHANGELOG.md) (latest update 1.6.3 on July 20, 2023) + - New `pg.fill_rectangle()` [examples and documentation](https://phidl.readthedocs.io/en/latest/geometry_reference.html#Fill-tool) # Citation diff --git a/docs/geometry_reference.ipynb b/docs/geometry_reference.ipynb index 2ace70d1..4577aac7 100644 --- a/docs/geometry_reference.ipynb +++ b/docs/geometry_reference.ipynb @@ -1215,12 +1215,12 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 29, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -2480,6 +2480,198 @@ "qp([D, waypoint_path, waypoint_path2])" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Fill tool" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In some cases it's useful to be able to fill empty spaces of your layout with dummy geometries, for example to increase fabrication uniformity or make easy ground planes. PHIDL has a fill tool that uses scikit-image to provide such functionality. \n", + "\n", + "### Dummy fill\n", + "\n", + "In this first example, we will create a simple photonic waveguide (e.g. an arc), by filling empty areas with rectangles on layer 4 and layer 3" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import phidl.geometry as pg\n", + "from phidl import Device, quickplot as qp\n", + "\n", + "# Create \"waveguide\" design\n", + "D = Device()\n", + "waveguide1 = D << pg.arc(radius=10, width = 2, theta = 135, layer = 0)\n", + "\n", + "# Create fill that avoids the waveguides\n", + "fill = pg.fill_rectangle(D = D,\n", + " fill_size= (1.5,1.5), # Basic cell size of the fill\n", + " avoid_layers=[0], # Layers that will be avoided\n", + " margin= 2, # Keepout distance from shapes\n", + " fill_layers= [4,3], # Adds fill rectangles to layer 4 and 3\n", + " fill_densities= [0.1,0.5], # Layer 4 filled 10%, layer 3 filled 50%\n", + " # - Note that 10% of (1.5,1.5) area = sqrt(0.1)*(1.5,1.5) = (0.47,0.47)\n", + " fill_inverted=[False,False], # Neither layer is inverted\n", + " bbox= [(-15,-5),(20,18)] )\n", + "D << fill\n", + "qp(D)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Ground fill\n", + "\n", + "For the ground fill, we will make several devices which we want to share a common ground. To achieve this, we will create a special \"include\" layer that will override the avoided layers and force the fill to overlap the grounding pad of our geometry.\n", + "\n", + "To begin, we'll define a structure with a blue contact pad on the top, and a red grounding pad on layer 50 on the bottom. Let's then make 3 of them evenly spaced:" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import phidl.geometry as pg\n", + "from phidl import Device, quickplot as qp\n", + "\n", + "def shape_with_ground_pad():\n", + " D = Device()\n", + " s = D << pg.snspd_expanded(layer = 0).rotate(-90)\n", + " contact_pad = D << pg.compass(size = (10,10), layer = 1)\n", + " ground_pad = D << pg.compass(size = (10,10), layer = 50)\n", + " contact_pad.connect('S',s.ports[1])\n", + " ground_pad.connect('N',s.ports[2])\n", + " return D\n", + "\n", + "def three_shapes_with_ground_pad():\n", + " Structures = Device()\n", + " s1 = Structures << shape_with_ground_pad()\n", + " s2 = Structures << shape_with_ground_pad()\n", + " s3 = Structures << shape_with_ground_pad()\n", + " group = s1 + s2 + s3\n", + " group.distribute(direction = 'x', spacing = 10)\n", + " return Structures\n", + "\n", + "qp(three_shapes_with_ground_pad())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we'll fill the empty areas (along with the \"include\" layer) with a solid ground plane" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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lLEQrpkpaiAbEzrUC0oVo04fVl8d7gFuA+xI3isgM4GHgi0ALsAnI/tdNpSxSqFXPSqVSzlc0lb1Y+knbGPMwgIisAuYl7LoC2GqMeSi+fx1wVEQWG2O6rGyDUpkQEQwGKdZH7QogIgX/xFiJ9BdEZaWCZNoicgswb/zyuIh8G6gyxnwq4ZgtwJeNMT+frB7NtFObTpl2v9/PuQmX/Rra2rj9nnveNCbZ+tgNf8uCj52GiBQk077+6qsZ7u2dKD+zcSPNdcd/dacQ45dqvD5/882WnJ/PP/88dz5zP8v/2vpMO914FSvTLsT59vdf+j94Lp1DQ3ujZZl2PuNlVdmKOjTTTq0cbq7iAXqTtg0CDckHishaYC3AvHnzbPFVh76+vqI+34UXXcQHliyZKH/jiSf43OWXZ1zO9jEjNTUAedWRT7tuuOSNu5U9GP8Hnq+5bbPx+mpwOBw0eLyWn2cNdXVcndDuUCRStPFLHi+rzs9AIMAcTzuegSpm17QRDoctG7d04zXVuTJSU0P95ZeX7fnW3txG1Vg9dYPVnDArt/e05Ncwn/GyqmxFHePjW+z30GKzsn/FmrR9gDdpmxcYTj7QGHM3cDfEPmnb5bevYrazp7ubpvnzJ8pdnZ00rV6dcTmXxxSijlzq7OnutmSsD/UdwVXbisPlZNg3ZPnrl+41SrWtEOPX091NS0uLJf3r6emhZ/gwLU0dHBzrxeVyWTZu2Z7TyduafL6yPd/6BvuornISaXSx99D+nOtLfFy+42VF2Yo6EsfXLu/1ubKqf8X6nvZWYMV4QUTqgYXx7UoVnUMcmKgGtNlwOHTMcuFwOHQhmrKMpZm2iLiIfXr/MrGFaH8LhIFm4DXg48ATwFeA1caYs6aqTzPt1KZTpp0uc9y2cydLFy2aKGeaQV574/XMWPMWXDXunDLt5EwxuR3lkjH2+/1c+aEP0dPdnbKd2WS2L730Ev/267s49YNvyzrTzne8ipVpF+J8u/GWm+BcL01zWzPKtJPHCiDiduMMhSbK+YyXVWUr6tBMO7ViZtpfIDZhj/sw8BVjzDoRWQN8B3iA2Pe0r7T4uaeN6fQ97VTl4/q+efNx5Uy/9+l0uSb+YEguhnt7p2zHFZs3F/w7rpnW+YElSyYupeY6XgBOpxMTye2X/HzHq1jf0y7E+eZ0ughFMj/XkscK4Kann+aWhMvK+YyXVWUr6tDvaWfP6q98rQPWTbLvN8BiK59PqVxVuVxEw5FSN8NWXC4XZDH5qJgqt5sxPdeURfTe42pacrurCIf0jTQbVVVVREM6aWeruqqGaFjHTVlD7z1uAc20rSlbUUem946++Vu3MHhqlMbZLTll2sV+DfKp8/zzz6erszPl/mzutb1//34+e/v/5YxrV2edaec7XqXKtK043779vdt5beZh5p7akVGmneo+9TMXLuTwrl05t9OKvmqmnbtyzrRVEUz3TNuKjKyhvoGjY0czOjaVYr8G+dT5ucsvn/iaTT6ZYm1tLZHRcMbHJ8p3vEqZaed7vnnrGwiN7Ut73LhU96m/6emnuavE/7Y00y4PenlcTUvNDU0ERsZK3Qxb8Xg8hEZD+vWlLDU3NBEcCZS6GapC6KStpqX25jYCQ6OlboatVFdXU+OqIjQaLHVTbKWluYXIsI6ZsoZO2mpaam9vJ9ofSn+gOs7s9ln4jr3pRoZqCm1tbUQGdNJW1tCFaBbQhWjWlCH9zSzSlTO9WUhPTw83fOufWHbV22y7EC15rCD1+Fx40UWW3FwF4I577mJrYzejvSMVsRCtGOfb0NAQH79xLav+z1/w56//Vhei6UK0tHQhWoWp5IVoX964kfsffTTNCORv1qxZOMeEgC+3XLscFqJlOlZWviEuO2kJz29+GWdNdm8d5boQrRjnm9frpaW+meHeoYyO14Voaip6eVxNSw6HgzOWruTwzgOlboqtLF26FP/uQYzR7x1n463LV3F4h55rKn86aatp6+wz3k5/15FSN8NW2tvbmds4i2N7k//SrprKWWe+jeEdx0rdDFUBNNO2gGbauZVTZbLZZqz58Pv9XHnth2ms8vKju+/P6rGlyLSTxyub/N7K8/ORRx/h3x66g3Uf+7ytMu1Snm/hcJgPXvsRgqEQv/jBz6Y8VjPtyqOZ9jRXKZl2sfLrydTV1TG7dSbD/dmvhi5Fpl3q8Rq35JQl1DpqsnpMOWTapRw/l8vF4recwss7tqQ9VjNtNRW9PK6mtZbGlvQHqeM0NjbiFmepm2E7bc0zSt0EVQF00lbTWpWrqtRNsB2Xy4WIlLoZtuN2u0vdBFUBNNO2gGbauZUz+WMLxhgGBgYYGxujoaEBh8PB4OAgbrebxsZGBgcHCYfDNDc3MzY2ht/vp76+nqqqKgYGBnC5XDQ1NTEwMEA4HMbr9RKJRPD5fNTW1vJvd/4Hr732Gj++74Ep25GsFJl2Nn/cIxAI0N/fj9PpZGxsjLq6OoLBII2NjUSjUYaHh6mpqaG+vp6BgQGMMTQ3NzMyMkIgEKC+vh6n0zkx1oljGA6HueYL13HDR663VaadyfgNDAwwOjqKx+PB5XIxMDBwXP9DoRDNzc0Eg0H8fj81NTXU1tZOjHVTUxNDQ0OEQiEaGhoAGBwcpLa2lgcf/inrN/6PZtqaaaelmXaFqaRMO53XX3+df1j3GV579TVWrTyT5qZmNjz3DDNntPG/3nkpP3vmUUYGfLz3Xe9my86tdL7cyekrT+fkExby643/TV11He+/8C957Nlf0XvoCO9afREHDvWw+eUXWXzKKVz0jgt4Lfxq2nYkK1WmnanbvvcdHvz1Q7jFzVXv+wg//90vOLDvAH/xzvMYGh7iz50vcOKCEzn3jLN55OnHCftD/NWlf8kfOp9n584dnLniDNpa2/jdH5+irWUG7zn3cn729KP4+od478Xv4dXOHXxn7M6MJ+1yybSncvDgQf7u859my5YtnLHyDDrmzefJjb+l0ePlivPfwyO//yX9vce47IJL2b13Ny90vsipy5dz+ikreOzpJ3Di5K/fdQVP/um37N+7j3POOodgMMBzL/6Jjvkd/OUF7yY0mP6+AJppq6no5XFV1kKhEJF6iFSDLzjCSNCPaRBCtVECwQBBT5RwVRR/wA8eJ0EJQ62DkYCfqNdBsCZMIBA7LlINvsAIYyZAtA6idcLlF19GfXVdqbtpudHQKJFGB4GqMOFIiHADRGsMvqCf4YAP0+AgXBNldGyMcCME3GFGA6NEPUKkCkaCo4wER8HrJFATIRgMEvTGxjpChMUrlhLNbi1a2QuHw0Q9DsLuKCFXhOHACDS+cQ6FvCZ2Do2NxMahKoqpj51rkUYhUB0mEAwQ9kC0GkaCI/iCfmhwEqkzvOOsdzCvbW6pu6lsTj9pq7LnH/IT9YcwBsZGx4j4wgScsU8soeEAkdEwxhh8A8NI2DAy5CNS30bEFyLoiN0EJDg0RsQfiv0SEI4QHQkzMli599A2xhAZCkI4Fn+NDvqJjkYYHfETjRoiw0FGh/0AhIeCmLHYn9wcGfDFx9oQGB0jPBwkSOwvVIWGYmMdjVbujVVGBoYxYxECYwHCoTDhoSCB6lh+HxwcJToaiwfG/GOYsSi+gWHMDEN4OIQJxcZlbMhPxB/GP+Inagzh4SD+IX8pu6UqiGbaFtBMO7dyJhljV1cXn/nnf+KUWSfx+pFu3OKirqqWI/5jnLf8bJ7Z+gdcYSftrW30DB5i5fzlvLRvC40uD/6xUQLOMOcvfydPbX2W+mg1uBwETJCl807h5X3buGPdf3Drrbfy/e9/f8p2JCv3TPuGmz7D7n17CDnCXHbWu3jiuf+mvaYFX8hP2ER4y6wOunpeY9VJK3lp1yuIgWVvWULn61tYOvcUdvbsokpcuJ1V9AcH+YtTz2HDlo24Qw5mz5zFwf7YTWkevf/nRRmvYmTa+/bt45ovXMdpc5fySk8XNcZNOBQm4HrjHHIHHFRVVzEqAU6du5TO/VtZ0DqfnqMHCUmEdy59Gxu3Pcechpn0+QeIGsO8GXPYdWQP3/js17j99tv53ve+l9VYgWbadmfbTFtEWoB7gXcBR4HPG2N+XMw2VILplGkDiDho9HohfvMyb4OXY2P9ADjEidvlIhwOxY9rREQIhyK4nG7C8U/aDnHQ4GlgeGwEgMYGL448VkCXe6YdCgVxO91EiP1S7hAHDQ1efH2xT3xeTyMOcRAJR3CKE4dDCAVjY9jkbYIe4sc1MDTgm6jD7XITDGb/19HskGlD7Fxramya6H+Dx0M4GLtnuEMc1NbWEolGAKHJ24hDhHA4jNvpJhr/ACTiwNvgpc8/AIDX48XRm/m5ppm2mkqxL4/fAQSBmcBK4AkR6TTGbC1yO5TNOCR5+YVM8v9T7EuYpGNfWarwry0JSMKFNIfjjf46Muz6m77aVeFDBin6TOK4OYgQif2/w/HGPgEmuWjpmA7nmiqaoi1EE5F6YA3wRWOMzxizEXgM+Eix2qCUUkrZWdEybRE5HfiDMaY2Yds/AquNMe9O2LYWWAvQ3t5+5g9/+MOitC8fg4ODNDY2Fu35bvvmNzHB4ER5yO/HW1eXcTnbx7TNns2uXbvyqiNVWaqq+PRnPztlX48cOcIvN/yaE2bM5cDRHhzipKHeQ59vgBNnnsCew3tx4qTaXcVIaJS3zOzg9cPdVBkXUQxhiUxs87jrCISChAmzYOYJ7D68l/dd9G5++ctf8jd/8zdTtiNZsV+DTMdr3C+e+AXDvhHChFl0wkns2PsarZ4mBkeGMSbK3Blz2Hv0AHOaZ3G4/wgiQqu3mcODR+lon8e+Iwdw4qC+tp6B0SEWzlrArkN7cOGkpqoaf3AUgKs+kNm45TteU41f2+zZ9B48mPf4DQwM8PCTj06cLy5i0ctoODCxrVqqiJoIISITY9JY48EfGCNswnS0z2fPkX20NbTS74t9/31WazsHjh3istUX8+yzz7JmzZqsxgrA09qK79gbf3CkGOdbMeocf02K/R5abNn279JLLy2LTNsDDCZtGwQaEjcYY+4G7obYQrRLLrmkOK3LQ7EXUfzkrrvelA/+OCk3mqqc7WMGPB4+/sc/5lVHqvKXN24k3evb1dXFT3/3CI3Njbx2dA9uXLhrqvAPj9HS0sK2Q69SbdxUu6rwB2PbthzaAdFqohjGHMGJbR5XPcFQiIAJ0tzSzNZDO3n729/Ohg0b0rYjWbFfg0zHa9wvf/sEQV+sr7NmzeLF7i3Mrq0mONJHmAjeZi/+3l3UN9Qz1h/EgVBTX4t/YIym5mZ2Hn6dKnHhrXbh98fG9ZWDscVZNa4aRgOxFeWZtiff8Zpq/AY8Hpp8vrzHb9++fTyw/sGJ86XGuHGKA79547xyiZNQNMSoBCfGpMndSDDwxnm17fCr1NTXEPAFiWLweBvwH93DqlWr+OMf/5h2zJLHCmKZ9nff8x5LxsuqshV1jL8muhAtc8X8nrYP8CZt8wKV+70bpZRSykLFnLR3Ai4ROTlh2wpAF6EppZRSGSjapG2MGQEeBm4WkXoRORt4L/CjYrVBKaWUsrNif+XrWuA+Yt+4PQZ8Sr/ulb1tO3dyxebNE+WDfX1ccdttGZezfcziFSvyriNV2enxZN7pMlPs1wCm93hNNX6JN1ephPFLHiuI3VzFqvGyqmxFHXZ5TcpJUSdtY0wf8L5iPmclmm43VwGIRg3RaJQoEaKR2E8k/mPESTgc/39jiEYjhMNhcAhRYtsikdi2aDRKJBo7dryOXG7LWe43V4lGTfy/0VifwxEi4WhC/6OxcYyPBQ4HURM7LhqNjUlUooTCoYlyJBLB4CIcDhOJROLfU86MXW6uAkycQ1ETO6+i0YRzKBomSmwMY2MbiY9ZFJMw1hP/H40SnRjr2BhmO1agN1dRb9B7j6uy5vF42PlKF7u3vsbY2BhVVdWMzB9hx+s7acHLjle2UV/jobmxiX2H9zODRrZ3bmNmSztRE6W3/yitppEdr2zHP3M+fQPH8Af8NNPA9s5tfO++uzk21FfqblpuycmLOfS7DWzbvoWlsxexY8t26AizZ383wXCIukgV21/ZRnXAxfadWxFxEB4OsWPXdprxsLVzCzXV1cydPZfXuncxgyZ2vLKdxjovDQ0NHDx6iFMWnJy+ITZSV1fHzle62L+jm8GRIZo8jXjq69l/uGei/7Na2gkEg/T7Bmh3NLP9pW0E549y8MhhRsdGaTD17NyyHZffsHP3a0SiUapCTrZv3caDDz3Iaz2vl7qbyuZ00lZlbd68eSw5dSkHDh7g5Dmn4BYXs1pn4mqq5tRlpzHo9FNt3Hjq6miY3cSpS0+l3+mjjmqiUUP7ibMntrXXtdLmbyNIiOVLlzPgHCFsItQ11Je6m5a7/prrePmFTpafeRodHR0sXbmche0d1Lc2EDYRlp28jBF3kKUnLoV6Jw4R3jJrAabBwbLFyxlxBahyuJnR2Ep1ax2nLjuVPscwNcZNlasK7+xmbvjIdaXupqVaW1tZcupSjvT2Mu+UDmqooraqmsa5rSxfupw+xzBeRz3BcJDZjhDLly3nmAwxp3EmzTNbCUSDLF+8jCGnn0WzF1LVVEvUGJacuISx6jBVNVU0zWxJ3xClpqCTtg1ppl16mmlnRzPtzGmmraaik7YNTcdMu9yUe6ZdbuyUaZeaZtpqKsX8nrZSSiml8qCTtlJKKWUTennchjTTLj3NtLOjmXbmNNNWU9FJ24Y00y49zbSzo5l25jTTVlPRy+NKKaWUTeikrZRSStmEXh63oWmbaRsDMlHAJNx+NBoxiQdijJn4/ykqPK6ObNgp035jLNIclzBWJmncEm/1aqKZ1ZfIfpm2meT/k8cmeZwmGxtDNMPXQTNtNRWdtG1oOmbaAgTDQcJEqK6uJmqi7O3ZN7H/6NGjROP//kPhMISieDwNmPAYe/fvJWpijxvtO0zEHTsuHI1w8MghnOLMuB3j7JRpHz12lKiJUFVdzejYKMYJ4nAQjobpOdQzcdyBgz1EorF7Y4fCQaImSlV1FVETYe+BfYxPUIPDg0TrJNVTTcpumXYoHIKIobHBSzRg2HtgH8ZEcVe7GfANEq2OjUUoEubwkSNU1VYBsP/AvolzbSwQAAe4XC7C0QgHEsZ6Kpppq6no5XFlE8Keg3vpHthHTU0NgWCAX/3xvwFondHKa0d2c9TfD8DBY4fZPbCP9lntADz2+18TiUbxeD3s6tnDweHDAPQNDfDS7ldwuir7d9cXul4iEA5SXV3N6z272T90EBFheMTHxi3PAeB0OvnT9hcYDAwB0H1oP3sG9lFXX0cwHOKXf/g1AO2zZ7Lr0G56R46VrD/FcKD3ILsH9tLU0kzURHl8468wGFpaW3n90B4OjfQCcGzwGDuOvIa3yQvA+ud/y2hoDJfbyev7X2fvYA/icOAb9fHUi78vZZdUhajsdytVEcYvzVbVVeOoj52y9Y0eXLVuXG4XDqfgrq2ixlsLQLWnmpBxIiLUeupwuB14mhoQEdz1VVTHj6vz1uGP+HE5s/+kXe6i0SjGGJwuJwYH9fWxyxDO2iqqvDUA1HprcY9WU1Vdhdvlwl1bRa03dh/2qrpqHHWxcfE01uOscVNdU43D4cBV554Y60ozfq5V19cQccY+TTc0eTHwxjlU66a6Idb/moY6AhLC6XRN7KtrjI2hq66KqoZqAOq9HtxD1ThdlXeuqeLSSduGplOmvWfPHrq2bmdmSzseRz3R0Sjtre149u7GE61lRl0Ls1pn4TG1NAbqaG1tpRkvPv8ws1tnMjw4hNftoT5Sw8yWdrymnrqxOma0ttEYrWdkdIiGuuxztXLPtL/2zVvZe3gfCxaeyNDQMI6wg/bWNpqlgSp/NW0tbXij9fSPVTGneRYulwuP1NIYqqN9RhstDi9hf5hZrTPZt38fDdTRXNXIzOZ2Gkw9jYE6GhoaMm6PHTLtI0eO0LV1O7OaZ+Kp9uL3jzK7dRZHj/TSVN1AXbiaWa2x/jfEz7WmqIeQf5TZLTNxhGGv7KEhXEd7SztN4sU96qK9ZQYN0TpqA27mNM/KeqxAM231Bsl0kUoprFq1ymzatKnUzUirp6eHOXPmFO35rnrve4ueaX/81lsLkmfd/+ijU/a1q6uLf/yXG/naDV9hxYoVUx6bq/Xr13PJJZdk9ZhivwaQ2XiNu+6z13Pk2FF+et9/Ff38TCXf8Uqbaft8eY/fvn37+NQXr+emtZ/jHe94R24dtUDyWEEs07519eqJciVl2vc/+mhZnKOFlG3/ROQFY8yqVPs001a2EM1xlfd0JaL/tHNVzh9klNJ/2arsRY0hHA6Xuhm24nK53vS1LZVe1BiCwWCpm6HUpCyZtEXkOhHZJCIBEbk/xf4LRKRLRPwiskFEOqx4XjU9hE2YY8cqe7Wy1Rq8DYSiIf1lJ0sRE+HI0d5SN0OpSVmSaYvIFUAUuBioNcZclbBvBrALuBp4HPgqcI4x5qx09Wqmndpblywh4vNNlA/29TG7pSXjcraPWbxiBRs2bMirjlRlp8fDn7Zvn7KvXV1d/N3XbmD1irP50j9+Ycpjc5VLpl3s1wAyG69xN3/rFp7p/AO3f/5bNDY2ljwvzHe8phq/xIVo+Yzfvn37+MT//RSnvWUp/7ruG7l11ALJYwWxhWiHd+2aKBfjfCtGneOviWbax5sq07Zk9bgx5uH4E60C5iXtvgLYaox5KH7MOuCoiCw2xnRZ8fzTzXS7uUrb/HZefnULIyMj1NfXZ/SYQrPDzVXqOrz8cdNzXHLBxVk9rhDscnOVllmt7Ondx9GjR5kxY0Z2nbSI3lxFTaUYX/laBnSOF4wxIyKyK779TZO2iKwF1gLMmzePnp7M7iJUSn19fUV9vjkdHQwkfFVi8YoVWZWzfcxITU3edaQqz+noSPv6Dg8P09E2H+Y4+POf/8yiRYumPD4Xg4ODWZ9nxX4Nxp8z03Y21ntZOX8lr+3cVfTzM5V8x2uq8RupqcnoMenGr7+/n/kz5uI8qYpNmzZx2mmn5dDT/CWPFcDcBQuKfr4Vo87x16QcztFCsrJ/xZi0PUBySDQIpPySpzHmbuBuiF0et8slk2K2s6e7m6b58yfKXZ2dNCV8HSRdOZfHFKKOnu7utOM2NDTEgcFDeJa00rVrB+edd96Ux+cil8vHpXgNMhmvcYMjQ4wsNOw7uhsRKfmlx3zHK934Nfl8eY9fJBJhf18PbUtO4KUdL2cdmVgleawADuzZQ1PHG0uBSvHvtdDvAaU+RwvNqv6lzbRF5Clg9SS7nzXGvDPh2FuAeUmZ9rcBtzHm2oRtrwDrjDE/n+q5NdNObbpl2rf85F/puGQxA4/t445bvz3l8bnIJNO+/uqrGe5943fPZzZupLmubqJcjpn24GmG3pcO8LFVH+D888/P6HFWSB4ryH+8ipVpf+6OL7L4g2ey654X+X+33ZdFr3OX7twCzbTtrqiZtjHmvMybltJW4KMJjakHFsa3qxxMt0wboKGtke1H/kQ4HMZVgnuFD/f2Hj/mmzcXPQ/MJf9zt9Vy9NjRrB+Xj+SxgvzHq1iZNkCtt46R4Ag+nw9PEe7Yle7cAs201Rus+sqXS0RqACfgFJEaERl/Z30EWC4ia+LHfAl4WRehqWw4XU7cnir6+/tL3RRbqW9t4NhgZeeFVhMRqptrOXq0uL/sKJUJq26u8gVgFLgR+HD8/78AYIzpBdYAXwP6gbcBV1r0vGoacXmqGBwcLHUzbKXWW8vQyFCpm2E7zgY911R50nuPW0Az7dzK2WTaKz72Dl7+z+f4zGXXsnLlykmPT5Wnbtu5k6UJq86Ty0d8PtoTLoMm74fCZrKZlnPJtOubPDg2DLPuc1/K6HHw5jFMN37J5VSZbCHzVKsz7TM+dS5bHt7E2rd+iLPPPnvS4yG38y3deKXqq2ba9lZ239NWxTUdM20AR7WT0dHRKY+ZLE9NzgwTy9c89tiU+8e3lToPzCX/c9W4Gc3ytpypMtZsy8XMU63OtAGk2pH2XIPczrd045Wqr5ppq3F673FlG1LlIBAIlLoZtuKqchMM6b20s+YSxsbGSt0Kpd5EJ21lG+ISQqFQqZthK063k0hE7z+eLUeVU3/ZUWVJM20LaKadWznbTHvr+s184ITLufTSSyc9PtV9m9O1o6a9nbEjRybdb0VfS5Vpzzx5Dgfu3sK/3/ItHI7Mfkcv5H3CC1FnITLtnc9s4YLqt3LlX0+9ZjaX8y2XvmqmbW+aaU9z0zXTxuEgEolMeUiq+zana8c1jz3Gj22QB+aS/4kIOGJ/jzzTSbuQ9wkvRJ0FybSdDkIZXKHI5XzLpa+aaatxenlc2YbEJx+VJUn/y446noiDSFTHTJUfnbSVbYhD9I00ByJQzjFYORLRXxBVedJJW9lG7NOPvpHmQieg7MR+QdQxU+VHF6JZQBei5VbOdiFa14ZXuKThHbx/zfsnPV4XosWML0SbtWguPT/Yxi2f/UrGf4tcF6Kdy+4/7WTlyEmsverqSY8HXYimC9EyowvRprnpuhBNJP0xuhAtf7oQLSaTDzS6EE0XohWbXh5X9iFCNFq+V4bKWTlfUStLmfyGqFQJ6KStbEYnH1V4scV7mmmr8qOZtgU0086tnG2mvfOZLVxY8zY+8P4PTHq8ZtoxyZn2zZ/5Mg0NDRk9VjPtc9mz6VVOHVzANR//5KTHg2bammlnRjPtaW66ZtqQ/jKvZtopZHmpVzPtGJPBVR3NtDXTLja9PK7KXjQaJegPEPQHNZvNQjgQIugPEAnpvcczZaImfq4FdP2EKkv6SVsV3bPPPENodJRXduzgqve+d8pjA2NjvLpnFzt+8hSRSIS+2S/x5I9/Munxr2zezFMjI8dtG0m6fGlHzz7zDK+89FLa8Rq3v2c//YP9ACxedip/98EPZnwb01c2b+bZaJSzzz035/aWi/FzDUh7voVCIXbtepVXf/F7IpEI+9tn8+fH109Zf/L55q6ttabhSk1CM20LaKadXdk3NESd201/IMBZJ554XJ11dXV8ec2azAYC+MrPf47f758oP7d7N83V1ccd0+PzMa+tbdJ22SHT9g0NEYhGjxuvTMdqwOOhaZJfXJLHD2JjWO1w4PF6S9LXbOucKtNucLmoc7sBinK++UMhhsNhzbQzLGumnZpm2hXG7pn2U08+yapZs/jw+vV88bTTjqvzqy+/nNkgxPn9/uPq+HBPDw9ccsnx7Xz8cdtn2k89+ST/8dJLx/U127FKJXn8IDaG/7ByJeddfHFOfSunTPvTp5zCqlmzYv0qwvm26dAhbtuxQzPtDMuaaWcv70xbRKpF5F4R6RaRYRF5UUQuTTrmAhHpEhG/iGwQkY58n1cppZSabqxYiOYC9gGrgUbgi8BPRWQBgIjMAB6Ob28BNgEPWvC8Siml1LRSkExbRF4GvmKM+bmIrAWuMsa8I76vHjgKnG6M6ZqqHs20U6uUTPvQyAizku6HnZw77uztZVFCHp1cTs4UU9VZKZn2UDB4XN9SZbSpxusvVq9m/7ZtKfenWgNwaGQEb1VVxWXaxTjfNNPWTDuVss60RWQmsAjYGt+0DOgc32+MGRGRXfHtU07aKrVKyrST8+fk3DFtOSlTTFVnJWXayX19Ux6dYrze39GBx+VKvT/FGoAPr19fsZl2oc83zbQ10y40SydtEXED/wn8MOFTtAfoTTp0EEh5e6b4J/O1APPmzaOnp8fKJhZEX19fUZ9vTkcHAx7PRHnxihVZlbN9zEhNTd51JJbdCxfia2piyRln4Js797g6k7flWwZYvmrVlO1qmz3b0vHKpJztY9wLF7LE4Ujb11TjMZbwySaT8Vpyxhm4Tzxx4rmL3dds6xypqZn0Me65c/E1NU3ZVyvPN3d9PYtraizv69wFC8r6Nci1PKejg56enqK/hxablf1LO2mLyFPE8upUnjXGvDN+nAP4ERAErks4xgd4kx7nBYZTVWiMuRu4G2KXx+1yyaSY7ezp7qZp/vyJcldnJ02rV2dczuUxVtYR2rULz6xZbN+8GU97+3F1Jm/LtwywZdMmmhI+DSW3q/fgweO+ElWI8cq3ztCuXWx/6aW0fU01HjWnn47nwIFJ96eq4+JolKaTTipJX3Ops8nnS/mYd42N4Yl/0i7G+RY6dIiuHTss7+uBPXto6ujIq45Sn8Opyj3d3RPvnXZ5r8+VVf2zJNMWEQHuAxYAlxljRhP2rQU+aow5O16uJ/bJ+wzNtHNTyZl28rZ8y1C5mXam43f+OeewffPmSfenqmO6ZNpWn2+aaWumnUo5Ztp3AUuACxMn7LhHgG+KyBrgCeBLwMvpJmw1uUrPtKfKDLMtQ2Vn2pmM39+ffvrEp8FMxmu6ZdpWnm+aaWumXWhWfE+7A/gksBI4JCK++M+HAIwxvcAa4GtAP/A24Mp8n1cppZSabvL+pG2M6Qam/DNCxpjfAIvzfS6llFJqOrPi5ipKKaWUKgL9gyEW0IVo2ZV1IVr2j9GFaLoQTRei2Vc5LkRTRaQL0XQh2mR91YVouhAt3XhZ2S5diFZ8enlcKaWUsgmdtJVSSimb0EzbApppZ1fWTDv7x2imrZm2Ztr2pZn2NKeZtmbak/VVM23NtNONl5Xt0ky7+PTyuFJKKWUTOmkrpZRSNqGZtgU0086urJl29o/RTFszbc207Usz7WlOM23NtCfrq2bammmnGy8r26WZdvHp5XGllFLKJnTSVkoppWxCM20LaKadXVkz7ewfo5m2ZtqaaduXZtrTnGbammlP1lfNtDXTTjdeVrZLM+3i08vjSimllE3oJ21VdO7aWjYdOoQ/FGLToUPH7Uvelm8ZQBz2/93UXVubUV9THbNrYIBQfFumdbhrawvRjaIbP9cg8/HKp1wp46bKl2baFtBM25pyqeq0Q6adT53nn38+XZ2dZdeuYmTaldJXzbTtrewybRF5ALgAqAcOAd8wxtyTsP8C4A7gBOB54CpjTLcVzz0d2T3TtqpdVtVph0w7nzo/d/nlNK1eXXbtKkamXSl91UxbjbPquuE/AwuMMV7gPcAtInImgIjMAB4Gvgi0AJuABy16XqWUUmrasGTSNsZsNcYExovxn4Xx8hXAVmPMQ8aYMWAdsEJEFlvx3EoppdR0YdkKHRG5U0T8QBdwEPhVfNcyoHP8OGPMCLArvl0ppZRSGbJ0IZqIOIG3A+cBXzfGhETkXqDXGHNjwnHPAt83xtyfoo61wFqAefPmnfn8889b1r5C6evroyVpgUYh3XPnnYwNDU2U9/X0MD9hkUO6craPaW5r4+XOzrzqKES7rKrzwNGjzJ0xo+zaZVWdp61YQX9vb9m1y6o6m9va6O/tLbt2WVlnxOnEGYmUXbvyraPG6+Xqa68t+ntosWXbv7lz5+a+EE1EngJWT7L7WWPMxIooY0wE2CgiHwY+BdwG+ABv0uO8wHCqCo0xdwN3Q2z1uF1WFBaznV+65ZaiPRfEVj5+1iavQy7Wr1/PJUk33agkujLX/qZDH7V/mUk7aRtjzsux3vFMeyvw0fEdIlIf37c1h3qVUkqpaSvvTFtE2kXkShHxiIhTRC4G/jfwu/ghjwDLRWSNiNQAXwJeNsZ05fvcSiml1HRixUI0Q+xS+H6gH/hX4B+MMY8CGGN6gTXA1+L73wZcacHzKqWUUtNK3jdXiU/Kk2Xe48f8BtCveCmllFJ5sP9NmZVSSqlpQidtpZRSyiZ00lZKKaVsQidtpZRSyiZ00lZKKaVsQidtpZRSyiZ00lZKKaVsQidtpZRSyiZ00lZKKaVsQidtpZRSyiZ00lZKKaVsQidtpZRSyibEGFPqNkxKRHqB7lK3IwMzgKOlbkQBaf/sTftnf5XeR+3f8TqMMW2pdpT1pG0XIrLJGLOq1O0oFO2fvWn/7K/S+6j9y5xeHldKKaVsQidtpZRSyiZ00rbG3aVuQIFp/+xN+2d/ld5H7V+GNNNWSimlbEI/aSullFI2oZO2UkopZRM6aedJRE4WkTEReSBp+wUi0iUifhHZICIdpWpjLkSkWkTuFZFuERkWkRdF5NKkY+zexxYReURERuL9/GCp25SPdK+Z3V+vcan+zVVK3wBE5EoR2R4/L3eJyDnx7bbvo4gsEJFfiUi/iBwSke+IiCu+z3b9E5HrRGSTiARE5P6kfZP2R2K+LiLH4j/fEBHJ5Dl10s7fHcCfEzeIyAzgYeCLQAuwCXiw+E3LiwvYB6wGGon15acisgAqpo93AEFgJvAh4C4RWVbaJuVl0tesQl6vccf9m6ukvonIRcDXgY8BDcC5wOsV1Mc7gSPAbGAlsXP1Whv3rwe4BbgvcWMG/VkLvA9YAZwG/C/gkxk9ozFGf3L8Aa4EfgqsAx5I2L4W+ENCuR4YBRaXus159vdlYE0l9DHe3iCwKGHbj4B/KXXbCvGa2f31Smj3m/7NVUrf4m3/A/CJFNsroo/AduCyhPI3ge/ZvX/EJu77M3294q/z2oT9nwCey+S59JN2jkTEC9wMfCbF7mVA53jBGDMC7IpvtyURmQksArbGN9m9j4uAiDFmZ8K2TuzT/rSSXjO7v15T/Zuzfd8ARMQJrALaROQ1Edkfv3xcS4X0Efg2cKWI1InIXOBSYD2V079x6fpz3H6yeO/RSTt3XwXuNcbsS7HPAwwmbRskdrnLdkTEDfwn8ENjTFd8s937aPf2TynFa1YJ/Z3s31wl9A1iMY0b+CvgHGKXj08HvkDl9PFpYpPTELCf2GXjX1A5/RuXrj/J+wcBTya5tk7aKYjIUyJiJvnZKCIrgQuBf5+kCh/gTdrmBYYL2OyspOtjwnEOYpeNg8B1CVWUfR/TsHv7JzXJa2br/qb5N2frviUYjf/3dmPMQWPMUeDfgMuogD7Gz8sniWW99cT+iEYzsQzf9v1Lkq4/yfu9gM/Er5VPRSftFIwx5xljZJKfdwLnAQuAvSJyCPhHYI2IbI5XsZXYAgMARKQeWMgbl5ZLLoM+Ev+t715inwDWGGNCCVWUfR/T2Am4ROTkhG0rsE/7U5riNbP763Uek/+bs3vfADDG9BP79JnqjbsS+tgCzAe+Y4wJGGOOAT8g9ktJJfQvUbr+HLefbN57Sh3g2/EHqANmJfz8K/AzoC2+v43Y5Y41QA2x3yQzWmRQTj/Ad4HnAE+KfbbvI/AT4L+I/dZ/drw/y0rdrkK8ZnZ/vab6N2f3viX182ZiK+PbiX0K/T2xWKAi+gi8DtxI7JsOTcAjxGIcW/Yv3o8a4J+JXd2qiW+bsj/ANcQW5c0F5hCbsK/J6DlL3elK+CFp9Xh824VAF7FLXk8BC0rdziz71EHsN/4xYpdyxn8+VEF9bCGWp40Ae4EPlrpNhXzN7P56JfX1uH9zldI3Ypn2ncAAcAi4DaiplD4Sy+mfAvqJ/X3ph4B2u/Yvfh6apJ916foDCPANoC/+8w3itxVP96P3HldKKaVsQjNtpZRSyiZ00lZKKaVsQidtpZRSyiZ00lZKKaVsQidtpZRSyiZ00lZKKaVsQidtpZRSyiZ00lZKKaVsQidtpZRSyib+f7AVm8UaTOKWAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Structures = three_shapes_with_ground_pad()\n", + "fill = pg.fill_rectangle(Structures,\n", + " fill_size= (1.5,1.5), # Basic cell size of the fill\n", + " avoid_layers=\"all\", # Layers that will be avoided\n", + " include_layers=50,\n", + " margin= 3,\n", + " fill_layers= [50],\n", + " fill_densities= [1.0],\n", + " fill_inverted=[False], \n", + " bbox= [(-30,-30),(80,35)] )\n", + "Structures << fill\n", + "qp(Structures)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Sometimes, for purposes of fabrication uniformity (or for superconductors, flux trapping), it's nice to punch \"holes\" in the ground plane. We can do that--while maintaining a contiguous plane--by changing the `fill_inverted` argument`:" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "Structures = three_shapes_with_ground_pad()\n", + "fill = pg.fill_rectangle(Structures,\n", + " fill_size= (3,3), # Basic cell size of the fill\n", + " avoid_layers=\"all\", # Layers that will be avoided\n", + " include_layers=50,\n", + " margin= 3,\n", + " fill_layers= [50],\n", + " fill_densities= [0.2],\n", + " fill_inverted=[True], \n", + " bbox= [(-30,-30),(80,35)] )\n", + "Structures << fill\n", + "qp(Structures)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -2496,7 +2688,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 61, "metadata": {}, "outputs": [ { @@ -2533,7 +2725,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 62, "metadata": {}, "outputs": [ { @@ -2567,7 +2759,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 63, "metadata": { "nbsphinx": "hidden" }, @@ -2593,7 +2785,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 64, "metadata": {}, "outputs": [ { @@ -2619,7 +2811,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 65, "metadata": {}, "outputs": [ { @@ -2645,7 +2837,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 66, "metadata": {}, "outputs": [ { @@ -2673,7 +2865,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 67, "metadata": {}, "outputs": [ { @@ -2699,7 +2891,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 68, "metadata": {}, "outputs": [ { @@ -2725,7 +2917,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 69, "metadata": {}, "outputs": [ { @@ -2760,7 +2952,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 70, "metadata": {}, "outputs": [ { @@ -2804,7 +2996,7 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 71, "metadata": {}, "outputs": [ { @@ -2831,7 +3023,7 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 72, "metadata": {}, "outputs": [ { @@ -2858,7 +3050,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 73, "metadata": {}, "outputs": [ { @@ -2884,7 +3076,7 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 74, "metadata": {}, "outputs": [ { @@ -2912,7 +3104,7 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 75, "metadata": {}, "outputs": [ { @@ -2940,14 +3132,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 76, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ - "
" + "
" ] }, "metadata": { @@ -2981,7 +3173,7 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 77, "metadata": {}, "outputs": [ { @@ -3011,7 +3203,7 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 78, "metadata": {}, "outputs": [ { @@ -3038,7 +3230,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 79, "metadata": {}, "outputs": [ { @@ -3065,7 +3257,7 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 80, "metadata": {}, "outputs": [ { @@ -3109,7 +3301,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.3" + "version": "3.7.6" } }, "nbformat": 4, diff --git a/phidl/device_layout.py b/phidl/device_layout.py index 39a8314d..cb495768 100644 --- a/phidl/device_layout.py +++ b/phidl/device_layout.py @@ -49,13 +49,12 @@ import gdspy.library import numpy as np from numpy import cos, mod, pi, sin, sqrt -from numpy.linalg import norm from phidl.constants import _CSS3_NAMES_TO_HEX gdspy.library.use_current_library = False -__version__ = "1.6.3" +__version__ = "1.6.4" # ============================================================================== @@ -111,23 +110,26 @@ def _reflect_points(points, p1=(0, 0), p2=(1, 0)): ------- A new set of points that are reflected across ``p1`` and ``p2``. """ - # From http://math.stackexchange.com/questions/11515/point-reflection-across-a-line - points = np.array(points) p1 = np.array(p1) p2 = np.array(p2) - if np.asarray(points).ndim == 1: - return ( - 2 * (p1 + (p2 - p1) * np.dot((p2 - p1), (points - p1)) / norm(p2 - p1) ** 2) - - points - ) - if np.asarray(points).ndim == 2: - return np.array( - [ - 2 * (p1 + (p2 - p1) * np.dot((p2 - p1), (p - p1)) / norm(p2 - p1) ** 2) - - p - for p in points - ] - ) + line_vec = p2 - p1 + line_vec_norm = np.linalg.norm(line_vec, axis=-1, keepdims=True) ** 2 + + # Checking if the input is 1D and adding an extra dimension if it is + input_was_1d = np.asarray(points).ndim == 1 + if input_was_1d: + points = np.array([points]) + + reflected_points_projection = ( + np.sum(line_vec * (points - p1), axis=-1, keepdims=True) / line_vec_norm + ) + reflected_points = 2 * (p1 + line_vec * reflected_points_projection) - points + + # If the input was 1D, remove the extra dimension from the output + if input_was_1d: + reflected_points = np.squeeze(reflected_points, axis=0) + + return reflected_points def _is_iterable(items): diff --git a/phidl/geometry.py b/phidl/geometry.py index ec7e4934..d1b8d4cd 100644 --- a/phidl/geometry.py +++ b/phidl/geometry.py @@ -3316,8 +3316,8 @@ def grid( If True, guarantees elements are speparated with a fixed spacing between; if False, elements are spaced evenly along a grid. shape : array-like[2] - x, y shape of the grid (see np.reshape). If no shape is given and the - list is 1D, the output is as if np.reshape were run with (1, -1). + x, y shape of the grid (as if np.reshape() were run with shape[::-1]). If no shape is given and the + list is 1D, the output is as if np.reshape were run with (-1, size of list). align_x : {'x', 'xmin', 'xmax'} Which edge to perform the x (column) alignment along align_y : {'y', 'ymin', 'ymax'} @@ -3335,9 +3335,8 @@ def grid( A Device containing all the Devices in `device_list` in a grid. """ - # Change (y,x) shape to (x,y) shape - shape = shape[::-1] device_array = np.asarray(device_list) + spacing = np.broadcast_to(spacing, 2) # Check arguments if device_array.ndim not in (1, 2): raise ValueError("[PHIDL] grid() The device_list needs to be 1D or 2D.") @@ -3351,12 +3350,15 @@ def grid( if (shape is None) and (device_array.ndim == 2): # Already in desired shape shape = device_array.shape elif (shape is None) and (device_array.ndim == 1): - shape = (device_array.size, -1) + shape = (-1, device_array.size) elif 0 < shape[0] * shape[1] < device_array.size: raise ValueError( "[PHIDL] grid() The shape is too small for all the items in device_list" ) else: + # Change (x,y) shape to (y,x) shape to follow default row, column format in np.reshape + shape = shape[::-1] + if np.min(shape) == -1: max_shape = np.max(shape) min_devices = int(np.ceil(device_array.size / max_shape) * max_shape) @@ -3773,7 +3775,7 @@ def _rasterize_polygons(polygons, bounds=[[-100, -100], [100, 100]], dx=1, dy=1) # Initialize the raster matrix we'll be writing to xsize = int(np.ceil(bounds[1][0] - bounds[0][0]) / dx) ysize = int(np.ceil(bounds[1][1] - bounds[0][1]) / dy) - raster = np.zeros((ysize, xsize), dtype=np.bool) + raster = np.zeros((ysize, xsize), dtype=bool) # TODO: Replace polygon_perimeter with the supercover version for n in range(len(xpts)): @@ -3809,15 +3811,13 @@ def _expand_raster(raster, distance=(4, 2)): return raster num_pixels = np.array(np.ceil(distance), dtype=int) - neighborhood = np.zeros( - (num_pixels[1] * 2 + 1, num_pixels[0] * 2 + 1), dtype=np.bool - ) + neighborhood = np.zeros((num_pixels[1] * 2 + 1, num_pixels[0] * 2 + 1), dtype=bool) rr, cc = draw.ellipse( num_pixels[1], num_pixels[0], distance[1] + 0.5, distance[0] + 0.5 ) neighborhood[rr, cc] = 1 - return morphology.binary_dilation(image=raster, selem=neighborhood) + return morphology.binary_dilation(image=raster, footprint=neighborhood) def _fill_cell_rectangle( diff --git a/setup.py b/setup.py index 39d57f0e..2ecf38ce 100644 --- a/setup.py +++ b/setup.py @@ -19,7 +19,7 @@ setup( name="phidl", - version="1.6.3", + version="1.6.4", description="PHIDL", long_description=long_description, long_description_content_type="text/markdown", diff --git a/tests/test_geometry.py b/tests/test_geometry.py index bb6fbcc2..88e5c7f4 100644 --- a/tests/test_geometry.py +++ b/tests/test_geometry.py @@ -265,3 +265,24 @@ def test_packer(): D = D_packed_list[0] h = D.hash_geometry(precision=1e-4) assert h == "d90e43693a5840bdc21eae85f56fdaa57fdb88b2" + + +def test_grid(): + device_list = [] + for width1 in [1, 6, 9]: + for width2 in [1, 2, 4, 8]: + D = pg.taper(length=10, width1=width1, width2=width2, layer=0) + device_list.append(D) + + D = pg.grid( + device_list, + spacing=(5, 1), + separation=True, + shape=(3, 4), + align_x="x", + align_y="y", + edge_x="x", + edge_y="ymax", + ) + h = D.hash_geometry(precision=1e-4) + assert h == "9228ee40016e508f5589effd50056df633357de2"