{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [], "authorship_tag": "ABX9TyOqoPlJxEzXB/rGffrk47H3", "include_colab_link": true }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" } }, "cells": [ { "cell_type": "markdown", "metadata": { "id": "view-in-github", "colab_type": "text" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "source": [ "# Ring Dataset for Calibration of Classification & Manifold Models" ], "metadata": { "id": "H-BUP1FKiX4R" } }, { "cell_type": "markdown", "source": [ "## defs" ], "metadata": { "id": "PBkKn7m0ydvB" } }, { "cell_type": "markdown", "source": [ "### optional download from github repo" ], "metadata": { "id": "t2ypmzGg6PaJ" } }, { "cell_type": "code", "source": [ "try:\n", " from gym_rings import get_rings\n", "except:\n", " !wget https://raw.githubusercontent.com/jcandane/gym_rings/main/gym_rings.py\n", " from gym_rings import get_rings" ], "metadata": { "id": "0MWhz-V36ZjT" }, "execution_count": 1, "outputs": [] }, { "cell_type": "markdown", "source": [ "### raw code" ], "metadata": { "id": "JiZ9NcKW6Xpi" } }, { "cell_type": "code", "source": [ "import numpy as np\n", "\n", "def define_ring(A, radii):\n", " \"\"\"\n", " define a Boolean ring, such that the image is made from \"True\" or \"1\".\n", " A:np.ndarray (initial array)\n", " radius_range:tuple defined by (minimum radius, maximum radius)\n", " GET>\n", " A:np.ndarray (initial array with an additional ring with radius_range)\n", " \"\"\"\n", " height, width = A.shape\n", " radii = radii.reshape(-1,2).T\n", "\n", " center = np.array([width / 2, height / 2])\n", " I_xi = np.indices((height, width)).reshape(2, -1) ## meshgrid -> flatten image\n", " I_xi = np.vstack((I_xi[1], I_xi[0]))\n", "\n", " ### RINGS\n", " mask_i = (np.linalg.norm(I_xi-center[:,None], axis=0)[:,None] >= radii[0][None,:]) ##&\n", " mask_i &= (np.linalg.norm(I_xi-center[:,None], axis=0)[:,None] < radii[1][None,:])\n", " mask_i = np.any(mask_i, axis=-1)\n", "\n", " A = A.reshape(-1)\n", " A[mask_i] = 1\n", " return A.reshape(height, width)\n", "\n", "def ring_notch(image_shape, θ:np.ndarray, radius_range, notch_width=5.):\n", " \"\"\"\n", " GIVEN>\n", " image_shape:tuple (The shape of the image (height, width))\n", " θ:np.ndarray[1d] (list of angles, θ.shape=(samples,))\n", " radius_range:np.ndarray (for a given ring, [R_min,R_max])\n", " notch_width:float (in degrees)\n", " GET>\n", " np.ndarray (A boolean mask for the notches)\n", " \"\"\"\n", " height, width = image_shape\n", "\n", " θ = (θ).astype(float)\n", " θ *= -1.\n", " #θ -= 1.*notch_width\n", " θ_min = np.deg2rad(θ - notch_width)\n", " θ_max = np.deg2rad(θ + notch_width)\n", "\n", " # Create a grid of x and y coordinates\n", " y, x = np.ogrid[:height, :width]\n", "\n", " # Calculate the distances and angles\n", " y = y - width / 2\n", " x = x - height / 2\n", " distance = np.sqrt(x**2 + y**2)\n", " angle = np.arctan2(y, x) ## every pixel associated an angle\n", "\n", " # Normalize angles to [0, 2*pi)\n", " angle = np.mod(angle, 2 * np.pi)\n", " θ_min = np.mod(θ_min, 2 * np.pi)\n", " θ_max = np.mod(θ_max, 2 * np.pi)\n", "\n", " # Create the mask for the angle range\n", " R_min, R_max = radius_range\n", " R_min = float(R_min)-0.01\n", " R_max = float(R_max)+0.01\n", "\n", " shifted_angle = (angle[:,:,None] - θ_min[None,None,:]) % 360 ### why not % 2*np.pi ???\n", " shifted_end_angle = (θ_max - θ_min) % 360\n", " angle_mask = (shifted_angle <= shifted_end_angle[None,None,:])\n", "\n", " radius_mask = (distance <= R_max) & (distance > R_min)\n", " mask = angle_mask & radius_mask[:,:,None]\n", " return mask.swapaxes(0,2).swapaxes(1,2) ### s.t. snapshots, pixels\n", "\n", "def get_rings(N:int, θs:np.ndarray, radii, notch_width=5.): ##\n", " \"\"\"\n", " GIVEN>\n", " N:int (image side size, such that image.shape=(N,N))\n", " θs:np.ndarray[2d] (list of angles for each ring, with θs.shape=(ring count, samples) )\n", " radii:np.ndarray[2] (with shape=(ring count, 2), i.e. axis=1 is the R_min, R_max for each ring)\n", " notch_width:float (notch angle, default=5 degrees, this can be generalized)\n", " GET>\n", " np.ndarray (dataset of shape=(θs.shape[1], N, N))\n", " \"\"\"\n", " img_shape = (N,N)\n", "\n", " R = define_ring(np.zeros(img_shape, dtype=bool), radii)\n", " mask = np.asarray([ ring_notch(img_shape, θs[r], radii[r], notch_width=notch_width) for r in range(len(radii))])\n", " mask = np.sum(mask, axis=0)\n", "\n", " return R[None,:,:]*np.logical_not( mask )" ], "metadata": { "id": "53embXj5iqV6" }, "execution_count": 2, "outputs": [] }, { "cell_type": "markdown", "source": [ "## Rings test" ], "metadata": { "id": "Jm3p1JlLqxO5" } }, { "cell_type": "code", "source": [ "import matplotlib.pyplot as plt\n", "\n", "### input\n", "N = 256\n", "angles = np.array([[90,270,180.,0,360,65,182, 234], [45,86,243,360,97,12, 311, 34], [90,270,90,5,156,65,182, 211]])\n", "radii = np.array([[30,50],[70,90],[110,130]])\n", "\n", "### ouput\n", "A = get_rings(N, angles, radii)\n", "\n", "plt.imshow(A[-8], interpolation='none', cmap='Greys')\n", "plt.axis(\"off\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 406 }, "id": "2by18XdLq1bh", "outputId": "e71e882d-e45e-479b-fb72-bb49f74efe99" }, "execution_count": 3, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "import matplotlib.pyplot as plt\n", "\n", "### input\n", "N = 64\n", "angles = 360*np.random.rand(3,100000)\n", "radii = np.array([[1,10],[15,30]]) #np.array([[30,50],[70,90],[110,130]])\n", "\n", "### ouput\n", "A = get_rings(N, angles, radii)\n", "\n", "\n", "print(A.size/1024/1024, A.dtype)\n", "plt.imshow(A[-8], interpolation='none', cmap='Greys')\n", "plt.axis(\"off\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 424 }, "id": "9KT-Nq39oJw_", "outputId": "27070a9b-8f0a-425b-c843-c28883e82282" }, "execution_count": 4, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "390.625 bool\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAGFCAYAAAASI+9IAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAHf0lEQVR4nO3dwW7bRhRAUarI//8yuyhwExRiFDm0ODM8Zxl0QVuULx7mlXzs+75vALBt2z9XXwAA4xAFACIKAEQUAIgoABBRACCiAEBEAYCIAgARBQAiCgBEFACIKAAQUQAgogBARAGAiAIAEQUAIgoARBQAiCgAEFEAIKIAQEQBgIgCAPlx9QVwH4/H4+pLWNK+71dfAgsxKQAQUQAgogBARAGAiAIAsX3ES7aGxnbW52OLiW0zKQDwC1EAIKIAQEQBgIgCALF9tDibQ/ypM+4VG0zzMykAEFEAIKIAQEQBgIgCALF9tAhbRozg6D60lTQPkwIAEQUAIgoARBQAiIPmQTk4ZiXv3M8Opa9lUgAgogBARAGAiAIAEQUAYvtoADaN4CePyriWSQGAiAIAEQUAIgoARBQAiO2jb2CbCM737vfKttLXmBQAiCgAEFEAIKIAQEQBgNg++gu2jGBcz76fNpJeMykAEFEAIKIAQEQBgIgCALF99IdsGsH8vNXtNZMCABEFACIKAEQUAIiD5v9xoAz34wD6J5MCABEFACIKAEQUAIgoAJDbbh/ZMgJeueNWkkkBgIgCABEFACIKAEQUAIgoABBRACCiAEBEAYCIAgARBQCy/LOPPOMIONvKz0QyKQAQUQAgogBARAGALHPQ7EAZuNqzv0OzHT6bFACIKAAQUQAgogBARAGAiAIAEQUAIgoARBQAiCgAEFEAIFM++8hzjtY32/NizuYeX8dsL+QxKQAQUQAgogBARAGAiAIAeeyjHoFvNjBWM/CtNjXfk7Vc/T0xKQAQUQAgogBARAGAiAIAmfLZR4zt6u2Juzn6fdtK4itMCgBEFACIKAAQUQAgDpp5ycHxnN793BxMs20mBQB+IQoARBQAiCgAEFEAIEO8ZMfWwxgGuBUYjO/mOD71/TQpABBRACCiAEBEAYCIAgDx7COmsto2jI0vRmNSACCiAEBEAYCIAgARBQBi++imRt96WW3L6MjRzznK53N0HXf5fO7IpABARAGAiAIAEQUAIgoA5KNvXrOx8HmjbLFsm8//u/iM7+s7PnuTAgARBQAiCgBEFACIKAAQUQAgogBARAGAiAIAEQUA4iU7i/Cog/sa6UU9XsozP5MCABEFACIKAEQUAIgoABDbR3yZjZKxjbSVxDxMCgBEFACIKAAQUQAgogBARAGAiAIAEQUAIgoARBQAiCgAEFEAIKIAQEQBgIgCABEFACIKAEQUAIgoABBRACCiAEBEAYD8uPoCYBT7vj/998fj8eErgeuYFACIKAAQUQAgogBARAGAiAIAEQUAIgoARBQAiCgAEFEAIKIAQEQBgIgCABEFACIKAEQUAIgoABBRACCiAEBEAYCIAgARBQAiCgBEFACIKAAQUQAgogBAflx9Acxr3/en//54PD58JTxz9PnA75gUAIgoABBRACCiAEBEAYDYPlrE0cbPFRsotpI+a4Yto3eu0X1yLZMCABEFACIKAEQUAIiDZm5nhoPZOzvr83Fg/TUmBQAiCgBEFACIKAAQUQAgj32AVQxbAp83wMf+W995T7z7s19xf876+Yx+3e8a6W/Tp363JgUAIgoARBQAiCgAEFEAIJ59dFPPtipG2hy5y4t6RvqdP/Pu7/ud/370n33b5thUO5tJAYCIAgARBQAiCgBEFACI7SOmcsXGygxbMjN6d1Nnhs/hjGu8eoPJpABARAGAiAIAEQUAIgoAZIg3rx25+hSe/wx8i3Ci1b5v7tuvMSkAEFEAIKIAQEQBgHjMBS+t+DiCO1jt4Phdo79IalQmBQAiCgBEFACIKAAQUQAgto843dHWi82P73H3LaN32KR7zaQAQEQBgIgCABEFACIKAGTol+wcsW2xvglvy1O5x+e0wn1rUgAgogBARAGAiAIAEQUAMuX20TO2NYARzfYn1qQAQEQBgIgCABEFACIKAEQUAIgoABBRACCiAEBEAYD8uPoCznL0v5J7/AXwKbM90uIZkwIAEQUAIgoARBQAiCgAkGW2j47YSgLOtsKW0RGTAgARBQAiCgBEFACIKAAQUQAgogBARAGAiAIAEQUAIgoAZPlnHx3xTCTglZWfcXTEpABARAGAiAIAEQUActuD5iMOoOF+7nigfMSkAEBEAYCIAgARBQAiCgDE9tEferadYCMJ5mLL6DWTAgARBQAiCgBEFACIKAAQ20d/wXOSYFw2jb7GpABARAGAiAIAEQUAIgoAxPbRN3h368G2Erxmm+gzTAoARBQAiCgAEFEAIKIAQGwfDcBb3eAnW0bXMikAEFEAIKIAQEQBgDhoHpRHZbASh8fzMCkAEFEAIKIAQEQBgIgCALF9tIij7Q5bSXySLaP5mRQAiCgAEFEAIKIAQEQBgNg+WtwZ2yA2mO7B5hDbZlIA4BeiAEBEAYCIAgARBQBi+4iXztpKscX0PWwNcSaTAgARBQAiCgBEFACIg2Y+xoEojM+kAEBEAYCIAgARBQAiCgBEFACIKAAQUQAgogBARAGAiAIAEQUAIgoARBQAiCgAEFEAIKIAQEQBgIgCABEFACIKAORfYbo0OJmrIksAAAAASUVORK5CYII=\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "## Pendulum Data Set" ], "metadata": { "id": "xIZtaQQp710J" } }, { "cell_type": "code", "source": [ "### download numpy zip file for pendulum trajectory\n", "try:\n", " angles = np.load(\"pendulum_L100m_1000s_90deg_a0_0014mss.npy\")[1]\n", "except:\n", " !wget https://raw.githubusercontent.com/jcandane/gym_rings/main/pendulum_L100m_1000s_90deg_a0_0014mss.npy\n", " angles = np.load(\"pendulum_L100m_1000s_90deg_a0_0014mss.npy\")[1] ## for angles, [0] are real time-stamps\n", "\n", "angles=np.array([angles])-90\n", "N = 32\n", "radii = np.array([[5,15]])\n", "\n", "### ouput data_set\n", "A = get_rings(N, angles, radii)" ], "metadata": { "id": "ppzst4Fjpje4" }, "execution_count": 5, "outputs": [] }, { "cell_type": "code", "source": [ "print(A.size/1024/1024, A.dtype)\n", "plt.imshow(A[0], interpolation='none', cmap='Greys')\n", "plt.axis(\"off\")\n", "plt.show()\n", "\n", "plt.imshow(A[-1], interpolation='none', cmap='Greys')\n", "plt.axis(\"off\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 813 }, "id": "AzxYEkL5AEGy", "outputId": "26a585a7-41d6-47c3-b726-7ec69366cfa2" }, "execution_count": 6, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "97.65625 bool\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [], "metadata": { "id": "W--VG00o83zE" }, "execution_count": 6, "outputs": [] } ] }