ImagePhaseSandbox.ipynb

frame0.jpg

frame30.jpg

ImagePhaseSandbox.ipynb

{
  "cells": [
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import astropy.coordinates as coord\nimport astropy.units as u\nimport matplotlib as mpl\nimport matplotlib.pyplot as plt\n%matplotlib inline\nimport numpy as np\n\n# from scipy.fftpack import rfft as fft, irfft as ifft\nfrom scipy.fftpack import fft2 as fft, ifft2 as ifft\nfrom PIL import Image as pil",
      "execution_count": 1,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# import cv2\n# vidcap = cv2.VideoCapture('/Users/apricewhelan/Downloads/48728220883_b87ea8cf30_vm.mp4')\n# success, image = vidcap.read()\n# count = 0\n# while success:\n#     if count == 0 or count == 31:\n#         cv2.imwrite(\"frame%d.jpg\" % count, image)     # save frame as JPEG file      \n#     success, image = vidcap.read()\n#     count += 1",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "rgbs = []\nfor filename in ['frame0.jpg', 'frame30.jpg']:\n    im = pil.open(filename)\n    rgb = np.array(im).astype(np.float64)\n    rgbs.append(rgb)",
      "execution_count": 3,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# for rgb in rgbs:\n#     fig, ax = plt.subplots(figsize=(10, 10))\n#     ax.imshow(rgb[..., 0], cmap='Greys')\n#     ax.set_aspect('equal')",
      "execution_count": 35,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "all_ffts = []\nfor rgb in rgbs:\n    for band in range(3):\n        all_ffts.append(fft(rgb[..., band]))\n    \n#     fig, ax = plt.subplots(figsize=(6, 6))\n#     ax.imshow(ifft(fft(rgb)), cmap='Greys')\n#     ax.set_aspect('equal')",
      "execution_count": 5,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def get_ims(data1, data2, nslice, save_dont_return=False):\n    f1 = np.stack((data1.real, data1.imag), axis=0)\n    f2 = np.stack((data2.real, data2.imag), axis=0)\n    \n    amp1 = np.abs(data1)\n    amp2 = np.abs(data2)\n    \n    uf1 = f1 / amp1[None]\n    uf2 = f2 / amp2[None]\n\n    cross = np.cross(uf1, uf2, axis=0)\n    theta2 = np.arcsin(cross)\n    thetas = np.linspace(0, theta2, nslice)\n    dtheta = thetas[1] - thetas[0]\n    \n    frames = np.concatenate((np.arange(-4*nslice, 0), \n                             np.arange(0, nslice),\n                             np.arange(nslice, nslice + 4*nslice)))\n    \n    ims = [] \n    for j, i in enumerate(frames):\n        theta = dtheta * i\n        if i < 0:\n            fac = amp1\n        elif i > nslice:\n            fac = amp2\n        else:\n            fac = (amp2 - amp1) / nslice * i + amp1\n        \n        R = np.array([[np.cos(theta), np.sin(theta)],\n                      [-np.sin(theta), np.cos(theta)]])\n        rot_f1 = np.einsum('ijnm,inm->jnm', R, uf1)\n            \n        rot_f1 *= fac\n        rot_f1 = rot_f1[0] + 1j*rot_f1[1]\n        rot_f1 = ifft(rot_f1).real\n        \n        if save_dont_return:\n            fig, ax = plt.subplots(figsize=(10, 8))\n            ax.imshow(rot_f1.real, cmap='Greys')\n            ax.set_aspect('equal')\n            ax.xaxis.set_visible(False)\n            ax.yaxis.set_visible(False)\n            fig.tight_layout()\n            fig.savefig(f'/Users/apricewhelan/projects/scratch/supernova-phase-bump/sn_frame_{j:03d}.png', \n                        dpi=150)\n            plt.close(fig)\n            \n        else:\n            ims.append(rot_f1)\n    \n    if not save_dont_return:\n        return np.array(ims)",
      "execution_count": 66,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import glob, os\nfor filename in glob.glob('/Users/apricewhelan/projects/scratch/supernova-phase-bump/*'):\n    num = int(filename.split('.')[0].split('_')[-1])\n    new_filename = '/Users/apricewhelan/projects/scratch/supernova-phase-bump/sn_frame_{:03d}.png'.format(num)\n    os.system('mv {} {}'.format(filename, new_filename))",
      "execution_count": 73,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "nslice = 16\nims = get_ims(all_ffts[0], all_ffts[3], nslice, save_dont_return=True)",
      "execution_count": 67,
      "outputs": []
    },
    {
      "metadata": {
        "scrolled": false,
        "trusted": true
      },
      "cell_type": "code",
      "source": "# for im in [ims[0], ims[nslice], ims[nslice+nslice], ims[-1]]:\n#     fig, ax = plt.subplots(figsize=(10, 8))\n#     ax.imshow(im.real, cmap='Greys')\n#     ax.set_aspect('equal')\n#     ax.xaxis.set_visible(False)\n#     ax.yaxis.set_visible(False)\n#     fig.tight_layout()",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# max_theta = np.arcsin(cross[2])\n\nR = np.array([[np.cos(theta), -np.sin(theta)],\n                  [np.sin(theta), np.cos(theta)]])\nR.shape",
      "execution_count": 113,
      "outputs": [
        {
          "data": {
            "text/plain": "(2, 2, 1584, 1860)"
          },
          "execution_count": 113,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "plt.figure(figsize=(10, 10))\nplt.imshow(ifft(amp1 * np.exp(1j * phase2)).real - rgbs[0][..., 0], cmap='Greys')\n# plt.colorbar()",
      "execution_count": 90,
      "outputs": [
        {
          "data": {
            "text/plain": "<matplotlib.image.AxesImage at 0x1c2f09e9b0>"
          },
          "execution_count": 90,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {