diff --git a/demo/Dragonfly-WISE.ipynb b/demo/Dragonfly-WISE.ipynb new file mode 100644 index 0000000..5550685 --- /dev/null +++ b/demo/Dragonfly-WISE.ipynb @@ -0,0 +1,562 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "83cb237f6cb21799", + "metadata": {}, + "source": [ + "# Demo: Applying the algorithm to PSFs with spikes\n", + "In this demo, we will use the alogirthm to match a Dragonfly g-band PSF witha WISE g-band PSF. Please note that these were compute a-priori. \n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "107175b216f439af", + "metadata": { + "ExecuteTime": { + "end_time": "2025-08-19T13:24:16.940362Z", + "start_time": "2025-08-19T13:24:15.629950Z" + } + }, + "outputs": [], + "source": [ + "from astropy.io import fits\n", + "import torch\n", + "from matplotlib import pyplot as plt\n", + "from dfpsf.utils import twodgauss_multimodal, convolve, twodgauss\n", + "from dfpsf.doubleKernel.matchingPSF import optimize_psf_langevin\n", + "import numpy as np\n", + "import cmcrameri.cm as cmc\n", + "import timeit \n", + "\n", + "device = 'cpu'" + ] + }, + { + "cell_type": "markdown", + "id": "3a6308f43cfa5744", + "metadata": {}, + "source": [ + "## Read the images\n", + "Let's start by reading in and visualizing the PSFs.\n", + "\n", + "**The data used in this example is proprietary. If you are interested in running it locally, please contact us!**" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "afc97f6b68a83de6", + "metadata": { + "ExecuteTime": { + "end_time": "2025-08-19T13:24:17.215403Z", + "start_time": "2025-08-19T13:24:17.017756Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "image1_path = '/home/carterrhea/Downloads/PSF-model-bullseye-dragonfly-g.fits'\n", + "image2_path = '/home/carterrhea/Downloads/wise-w3-psf-wpro-09x09-05x05-resampled.fits'\n", + "psf1 = fits.getdata(image1_path)\n", + "psf2 = fits.getdata(image2_path)\n", + "psf1 = np.asarray(psf1, dtype=np.float32)\n", + "psf2 = np.asarray(psf2, dtype=np.float32)\n", + "psf1[psf1<1e-8] = 1e-8\n", + "psf2[psf2<1e-8] = 1e-8\n", + "fig, axs = plt.subplots(1, 2, figsize=(10, 16)) # 2 rows, 2 columns\n", + "\n", + "# First plot: Original image\n", + "im = axs[0].imshow(np.log10(psf1), origin='lower', cmap=cmc.lajolla)\n", + "axs[0].set_title('Dragonfly g-band PSF')\n", + "fig.colorbar(im, ax=axs[0], fraction=0.046, pad=0.04)\n", + "\n", + "# Second plot: 2D PSF model\n", + "im = axs[1].imshow(np.log10(psf2), origin='lower', cmap=cmc.lajolla)\n", + "axs[1].set_title('WISE g-band PSF')\n", + "fig.colorbar(im, ax=axs[1], fraction=0.046, pad=0.04)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "7711913b914a7a8d", + "metadata": {}, + "source": [ + "There are a few clear things to note about these PSFs compared to the ones we've seen previously:\n", + " \n", + " - they are much larger\n", + "\n", + " - they have elevated backgrounds\n", + "\n", + " - they have strong diffraction spikes\n", + "\n", + "`dfpsf` is designed to match the bright portion of the PSFs using a linear combination of elliptical Gaussians. Therefore, it is unrealistic to expect `dfpsf` to be able to match the diffraction spikes (it's another question as to why you may want to do that). Instead, we can expect `dfpsf` to nicely match the central regions of the PSFs." + ] + }, + { + "cell_type": "markdown", + "id": "312c8d62da93e6f4", + "metadata": {}, + "source": [ + "And now we can mach the PSFs and see how they look using our `optimize_psf_langevin` function. We will use a multimodal Gaussian with 4 components for this example. We will also use a slightly larger kernel size to make sure that we aren't missing any structure. Since the PSFs are quite different, we will train for 20000 steps to make sure that the model has time to converge." + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "781ea314bfc3287d", + "metadata": { + "ExecuteTime": { + "end_time": "2025-08-19T13:25:03.859644Z", + "start_time": "2025-08-19T13:24:22.579302Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/carterrhea/Documents/dfpsf/src/dfpsf/loss.py:43: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.detach().clone() or sourceTensor.detach().clone().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " dx_mean = torch.mean(torch.tensor(dx_list))\n", + "/home/carterrhea/Documents/dfpsf/src/dfpsf/loss.py:44: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.detach().clone() or sourceTensor.detach().clone().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " dy_mean = torch.mean(torch.tensor(dy_list))\n", + "/home/carterrhea/Documents/dfpsf/src/dfpsf/loss.py:45: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.detach().clone() or sourceTensor.detach().clone().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " penalty = torch.sum((torch.tensor(dx_list) - dx_mean) ** 2) + torch.sum(\n", + "/home/carterrhea/Documents/dfpsf/src/dfpsf/loss.py:46: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.detach().clone() or sourceTensor.detach().clone().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " (torch.tensor(dy_list) - dy_mean) ** 2\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Step 1000: Loss = 33.877445, Best = 33.877445\n", + "Step 2000: Loss = 2.739254, Best = 2.739254\n", + "Step 3000: Loss = 0.518641, Best = 0.518641\n", + "Step 4000: Loss = 0.159900, Best = 0.159900\n", + "Step 5000: Loss = 0.096426, Best = 0.096426\n", + "Step 6000: Loss = 0.082029, Best = 0.082029\n", + "Step 7000: Loss = 0.076419, Best = 0.076419\n", + "Step 8000: Loss = 0.074787, Best = 0.074787\n", + "Step 9000: Loss = 213.086639, Best = 0.074024\n", + "Step 10000: Loss = 243.516602, Best = 0.074024\n", + "Elapsed time: 59.8978 seconds\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_447190/550733555.py:22: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.detach().clone() or sourceTensor.detach().clone().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " k1_params = torch.tensor(params[2:2+param_offset], device=device, dtype=torch.float32)\n", + "/tmp/ipykernel_447190/550733555.py:28: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.detach().clone() or sourceTensor.detach().clone().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " weight1_list = torch.tensor(params[2+param_offset:2+param_offset+n_components], device=device, dtype=torch.float32)\n", + "/tmp/ipykernel_447190/550733555.py:31: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.detach().clone() or sourceTensor.detach().clone().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " k2_params = torch.tensor(params[2+param_offset+n_components:2+2*param_offset+n_components], device=device)\n", + "/tmp/ipykernel_447190/550733555.py:37: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.detach().clone() or sourceTensor.detach().clone().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " weight2_list = torch.tensor(params[2+2*param_offset+n_components:2+2*param_offset+2*n_components], device=device)\n" + ] + } + ], + "source": [ + "psf1 = psf1-np.min(psf1)\n", + "psf2 = psf2-np.min(psf2)\n", + "\n", + "size = 9\n", + "use_multimodal = True # Set to True to use multimodal Gaussian\n", + "n_components = 4 # Number of Gaussian components for multimodal\n", + "\n", + "start = timeit.default_timer()\n", + "psf1_tensor = torch.tensor(psf1, dtype=torch.float32, device=device)\n", + "psf2_tensor = torch.tensor(psf2, dtype=torch.float32, device=device)\n", + "best_params, _ = optimize_psf_langevin(psf1_tensor, psf2_tensor, cen=size, n_steps=20000, use_multimodal=use_multimodal, n_components=n_components)\n", + "# Extract parameters based on the model type\n", + "if use_multimodal:\n", + " # Extract multimodal Gaussian parameters\n", + " params = best_params\n", + " s1, o1 = params[0], params[1]\n", + "\n", + " # Calculate parameter indices\n", + " param_offset = 5 * n_components # Each component has dx, dy, sig, q, pa\n", + "\n", + " # Extract parameters for kernel 1 (multimodal)\n", + " k1_params = torch.tensor(params[2:2+param_offset], device=device, dtype=torch.float32)\n", + " dx1_list = torch.tensor([k1_params[i*5] for i in range(n_components)], device=device, dtype=torch.float32)\n", + " dy1_list = torch.tensor([k1_params[i*5+1] for i in range(n_components)], device=device, dtype=torch.float32)\n", + " sig1_list = torch.tensor([k1_params[i*5+2] for i in range(n_components)], device=device, dtype=torch.float32)\n", + " q1_list = torch.tensor([k1_params[i*5+3] for i in range(n_components)], device=device, dtype=torch.float32)\n", + " pa1_list = torch.tensor([k1_params[i*5+4] for i in range(n_components)], device=device, dtype=torch.float32)\n", + " weight1_list = torch.tensor(params[2+param_offset:2+param_offset+n_components], device=device, dtype=torch.float32)\n", + "\n", + " # Extract parameters for kernel 2 (multimodal)\n", + " k2_params = torch.tensor(params[2+param_offset+n_components:2+2*param_offset+n_components], device=device)\n", + " dx2_list = torch.tensor([k2_params[i*5] for i in range(n_components)], device=device)\n", + " dy2_list = torch.tensor([k2_params[i*5+1] for i in range(n_components)], device=device)\n", + " sig2_list = torch.tensor([k2_params[i*5+2] for i in range(n_components)], device=device)\n", + " q2_list = torch.tensor([k2_params[i*5+3] for i in range(n_components)], device=device)\n", + " pa2_list = torch.tensor([k2_params[i*5+4] for i in range(n_components)], device=device)\n", + " weight2_list = torch.tensor(params[2+2*param_offset+n_components:2+2*param_offset+2*n_components], device=device)\n", + "\n", + "else:\n", + " # Unpack Gaussian parameters (original structure)\n", + " s1, o1, dx_mc, dy_mc, sig1_mc, q1_mc, pa1_mc, sig2_mc, q2_mc, pa2_mc = best_params\n", + "end = timeit.default_timer()\n", + "print(f\"Elapsed time: {end - start:.4f} seconds\")" + ] + }, + { + "cell_type": "markdown", + "id": "3bd233671e39abcc", + "metadata": {}, + "source": [ + "By examining the loss value, we see that the method quickly converges to a decent solution after about 8000 steps. The subsequent steps allow the algorithm to refine the solution. It eventually jumps (since it is meant to explore the full space), but this is expected behavior.\n", + "\n", + "In the next step we will use our solution to reconstruct the kernels. Again, we are using a multimodal Gaussian with 4 components in this example." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "a51f561fbc5ad155", + "metadata": { + "ExecuteTime": { + "end_time": "2025-08-19T13:25:03.878177Z", + "start_time": "2025-08-19T13:25:03.874436Z" + } + }, + "outputs": [], + "source": [ + "if use_multimodal:\n", + " # Create multimodal Gaussian kernels\n", + " kernel1 = twodgauss_multimodal(\n", + " dx1_list, dy1_list, sig1_list, q1_list, pa1_list,\n", + " weight1_list, cen=size, device=device\n", + " )\n", + " kernel2 = twodgauss_multimodal(\n", + " dx2_list, dy2_list, sig2_list, q2_list, pa2_list,\n", + " weight2_list, cen=size, device=device\n", + " )\n", + "\n", + "else:\n", + " kernel1 = twodgauss(dx_mc,dy_mc,sig1_mc,q1_mc,pa1_mc,cen=size, device=device)\n", + " kernel2 = twodgauss(torch.tensor(0), torch.tensor(0),sig2_mc,q2_mc,pa2_mc, cen=size, device=device)\n", + "best_fit1 = s1*convolve(psf1_tensor, kernel1) + o1\n", + "best_fit2 = convolve(psf2_tensor, kernel2)" + ] + }, + { + "cell_type": "markdown", + "id": "649e61b102834551", + "metadata": {}, + "source": [ + "With those calculations out of the way, let's go ahead and visual the kernels and the resulting convolutions." + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "845888c5de8fce1f", + "metadata": { + "ExecuteTime": { + "end_time": "2025-08-19T13:25:05.075997Z", + "start_time": "2025-08-19T13:25:03.925369Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axs = plt.subplots(3, 2, figsize=(8,8))\n", + "# Define the images and titles\n", + "images = [\n", + " (psf1, \"PSF 1\"),\n", + " (psf2, \"PSF 2\"),\n", + " (kernel1, \"Kernel 1\"),\n", + " (kernel2, \"Kernel 2\"),\n", + " (best_fit1, \"Convolution 1\"),\n", + " (best_fit2, \"Convolution 2\"),\n", + "]\n", + "\n", + "# Process images in pairs\n", + "for i in range(0, len(images), 2):\n", + " # Get the pair of images\n", + " img1, title1 = images[i]\n", + " img2, title2 = images[i+1]\n", + " img1 = img1 #/ img1.max()\n", + " img2 = img2 #/ img2.max()\n", + " if i == 1:\n", + " img1 = s1* img1 + o1\n", + " # Find shared min and max for the pair\n", + " vmin = min(img1.min(), img2.min())\n", + " vmax = max(img1.max(), img2.max())\n", + "\n", + " # Plot both images with shared limits\n", + " try:\n", + " im1 = axs[i//2, 0].imshow(img1.cpu().numpy(), origin=\"lower\", vmin=vmin, vmax=vmax, cmap=cmc.lipari)\n", + " im2 = axs[i//2, 1].imshow(img2.cpu().numpy(), origin=\"lower\", vmin=vmin, vmax=vmax, cmap=cmc.lipari)\n", + " except AttributeError:\n", + " im1 = axs[i//2, 0].imshow(img1, origin=\"lower\", vmin=vmin, vmax=vmax, cmap=cmc.lipari)\n", + " im2 = axs[i//2, 1].imshow(img2, origin=\"lower\", vmin=vmin, vmax=vmax, cmap=cmc.lipari)\n", + "\n", + " # Set titles\n", + " axs[i//2, 0].set_title(title1)\n", + " axs[i//2, 1].set_title(title2)\n", + "\n", + " # Add colorbars\n", + " fig.colorbar(im1, ax=axs[i//2, 0], fraction=0.046, pad=0.04)\n", + " fig.colorbar(im2, ax=axs[i//2, 1], fraction=0.046, pad=0.04)\n", + "plt.tight_layout()\n", + "plt.savefig('example1-SGLD.png', dpi=600, bbox_inches='tight')" + ] + }, + { + "cell_type": "markdown", + "id": "e80e9839", + "metadata": {}, + "source": [ + "It's a little tough to gauge how well the centers look when looking at the full size. So now we will look just around the center regions." + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "6f101905", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axs = plt.subplots(3, 2, figsize=(8,8))\n", + "# Define the images and titles\n", + "cut_val = 35\n", + "images = [\n", + " (psf1[cut_val:-cut_val, cut_val:-cut_val], \"PSF 1\"),\n", + " (psf2[cut_val:-cut_val, cut_val:-cut_val], \"PSF 2\"),\n", + " (kernel1, \"Kernel 1\"),\n", + " (kernel2, \"Kernel 2\"),\n", + " (best_fit1[cut_val:-cut_val, cut_val:-cut_val], \"Convolution 1\"),\n", + " (best_fit2[cut_val:-cut_val, cut_val:-cut_val], \"Convolution 2\"),\n", + "]\n", + "\n", + "# Process images in pairs\n", + "for i in range(0, len(images), 2):\n", + " # Get the pair of images\n", + " img1, title1 = images[i]\n", + " img2, title2 = images[i+1]\n", + " img1 = img1 #/ img1.max()\n", + " img2 = img2 #/ img2.max()\n", + " if i == 1:\n", + " img1 = s1* img1 + o1\n", + " # Find shared min and max for the pair\n", + " vmin = min(img1.min(), img2.min())\n", + " vmax = max(img1.max(), img2.max())\n", + "\n", + " # Plot both images with shared limits\n", + " try:\n", + " im1 = axs[i//2, 0].imshow(img1.cpu().numpy(), origin=\"lower\", vmin=vmin, vmax=vmax, cmap=cmc.lipari)\n", + " im2 = axs[i//2, 1].imshow(img2.cpu().numpy(), origin=\"lower\", vmin=vmin, vmax=vmax, cmap=cmc.lipari)\n", + " except AttributeError:\n", + " im1 = axs[i//2, 0].imshow(img1, origin=\"lower\", vmin=vmin, vmax=vmax, cmap=cmc.lipari)\n", + " im2 = axs[i//2, 1].imshow(img2, origin=\"lower\", vmin=vmin, vmax=vmax, cmap=cmc.lipari)\n", + "\n", + " # Set titles\n", + " axs[i//2, 0].set_title(title1)\n", + " axs[i//2, 1].set_title(title2)\n", + "\n", + " # Add colorbars\n", + " fig.colorbar(im1, ax=axs[i//2, 0], fraction=0.046, pad=0.04)\n", + " fig.colorbar(im2, ax=axs[i//2, 1], fraction=0.046, pad=0.04)\n", + "plt.tight_layout()\n", + "plt.savefig('example1-SGLD.png', dpi=600, bbox_inches='tight')" + ] + }, + { + "cell_type": "markdown", + "id": "257e45b8bd42b961", + "metadata": {}, + "source": [ + "As we can see the result is very promising! We are getting minimal convolution. Importantly, kernel 2 is very peaked while kernel 1 is recognizing the fact that it must have a non-negligible position angle in order to get the images to match! There is some additional emission in the outskirts of the convolution which is mainly driven by the larger wings in the WISE PSF." + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "abf90ed6604ca629", + "metadata": { + "ExecuteTime": { + "end_time": "2025-08-19T13:25:05.181700Z", + "start_time": "2025-08-19T13:25:05.093308Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Relative Error Between Convolution')" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "res = 100*(best_fit2.cpu().numpy()-best_fit1.cpu().numpy())/best_fit1.cpu().numpy()\n", + "plt.imshow(res[1:-1, 1:-1], origin='lower', cmap=cmc.roma, vmin=-100, vmax=100)\n", + "cbar = plt.colorbar()\n", + "cbar.set_label('Relative Error (%)', rotation=270)\n", + "plt.title(\"Relative Error Between Convolution\")" + ] + }, + { + "cell_type": "markdown", + "id": "5711325f", + "metadata": {}, + "source": [ + "Again, this is kind of hard to see what `dfspsf` is really doing since so much of the error comes from either noise, diffraction spikes, or the long wings. \n", + "\n", + "Let's check out the central region. We will also plot the relative error pre-convolution for comparison" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "d87288a2", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_447190/3677647377.py:4: RuntimeWarning: divide by zero encountered in divide\n", + " res1 = 100 * (psf2 - psf1) / psf1\n", + "/tmp/ipykernel_447190/3677647377.py:4: RuntimeWarning: invalid value encountered in divide\n", + " res1 = 100 * (psf2 - psf1) / psf1\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 2, figsize=(12, 5))\n", + "\n", + "# --- First plot ---\n", + "res1 = 100 * (psf2 - psf1) / psf1\n", + "im1 = axes[0].imshow(\n", + " res1[cut_val:-cut_val, cut_val:-cut_val],\n", + " origin='lower',\n", + " cmap=cmc.roma,\n", + " vmin=-100,\n", + " vmax=100\n", + ")\n", + "axes[0].set_title(\"Relative Error Between original PSFs\")\n", + "\n", + "cbar1 = fig.colorbar(im1, ax=axes[0], shrink=0.925)\n", + "cbar1.set_label('Relative Error (%)', rotation=270, labelpad=15)\n", + "\n", + "# --- Second plot ---\n", + "res2 = 100 * (best_fit2.cpu().numpy() - best_fit1.cpu().numpy()) / best_fit1.cpu().numpy()\n", + "im2 = axes[1].imshow(\n", + " res2[cut_val:-cut_val, cut_val:-cut_val],\n", + " origin='lower',\n", + " cmap=cmc.roma,\n", + " vmin=-100,\n", + " vmax=100\n", + ")\n", + "axes[1].set_title(\"Relative Error Between matched PSFs\")\n", + "\n", + "cbar2 = fig.colorbar(im2, ax=axes[1], shrink=0.925)\n", + "cbar2.set_label('Relative Error (%)', rotation=270, labelpad=15)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "892a8047", + "metadata": {}, + "source": [ + "This plot shows that, in the central regions of the PSF, this method really shines at matching the PSFs." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cc4dc793", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "dragonfly", + "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": "3.11.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}