{ "cells": [ { "cell_type": "markdown", "id": "cell-00", "metadata": {}, "source": [ "# DeepExtractor — Training Tutorial\n", "\n", "This notebook trains a fresh `DeepExtractor` (U-Net 2D) model from scratch on a small synthetic\n", "(`numpy`) noise dataset, plots the training and validation losses, and then tests the trained model\n", "on held-out sine-Gaussian injections.\n", "\n", "**What synthetic noise means here:** the background noise is white Gaussian noise scaled to match\n", "the variance of a whitened PyCBC noise realization (half the sampling rate). Use `--bilby-noise` / `bilby_noise=True` in order to train or use models corresponding to whitened detector noise aligning with theoretical O4 noise curves. In this case, the noise has zero mean and unit variance.\n", "\n", "**Pipeline overview:**\n", "1. Generate synthetic time-domain data (noisy glitch + background pairs)\n", "2. Convert to STFT spectrograms (magnitude + phase)\n", "3. Train the U-Net on spectrogram pairs\n", "4. Plot losses\n", "5. Test on sine-Gaussian injections" ] }, { "cell_type": "code", "execution_count": 1, "id": "cell-01", "metadata": {}, "outputs": [], "source": [ "import os\n", "import numpy as np\n", "import torch\n", "import torch.nn as nn\n", "import torch.optim as optim\n", "import matplotlib.pyplot as plt\n", "from sklearn.preprocessing import StandardScaler\n", "from torch.optim.lr_scheduler import ReduceLROnPlateau\n", "\n", "import warnings\n", "warnings.filterwarnings(\"ignore\", \"Wswiglal-redir-stdio\")\n", "\n", "from deepextractor.models.architectures import UNET2D\n", "from deepextractor.generation.generate_timeseries import (\n", " generate_gaussian_noise, generate_synthetic_data, LENGTH, SAMPLE_RATE, T\n", ")\n", "from deepextractor.generation.glitch_functions import generate_sine_gaussian\n", "from deepextractor.utils.signal import whitened_snr_scaling\n", "from deepextractor.training.train_fn import train_fn\n", "from deepextractor.utils.io import check_accuracy\n" ] }, { "cell_type": "markdown", "id": "cell-02", "metadata": {}, "source": [ "## Configuration" ] }, { "cell_type": "code", "execution_count": 2, "id": "cell-03", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Using device: mps\n" ] } ], "source": [ "# Device — uses MPS on Apple Silicon, CUDA on Linux/Windows GPU, otherwise CPU\n", "if torch.cuda.is_available():\n", " DEVICE = \"cuda\"\n", "elif torch.backends.mps.is_available():\n", " DEVICE = \"mps\"\n", "else:\n", " DEVICE = \"cpu\"\n", "print(f\"Using device: {DEVICE}\")\n", "\n", "# Dataset size — keep small for a quick demo; increase for real training\n", "N_TRAIN = 1000\n", "N_VAL = 200\n", "\n", "# Training\n", "BATCH_SIZE = 32\n", "EPOCHS = 50 # maximum epochs; early stopping may stop sooner however, this specific architecture will likely converge at a much higher epoch\n", "LR = 1e-4\n", "LR_PATIENCE = 4 # epochs without improvement before LR is reduced\n", "LR_FACTOR = 0.1 # factor to reduce LR by\n", "EARLY_STOPPING_PATIENCE = 9 # epochs without improvement before training stops\n", "\n", "# STFT parameters\n", "# Original DeepExtractor (arXiv:2501.18423): N_FFT=512, WIN_LENGTH=64, HOP_LENGTH=32\n", "# → produces (257, 257) spectrograms, richer time-frequency representation\n", "# but significantly slower to train.\n", "# Tutorial default: smaller spectrograms for faster training, but still gives decent performance (please see 129x129 model in the paper).\n", "N_FFT = 256\n", "WIN_LENGTH = N_FFT // 2\n", "HOP_LENGTH = WIN_LENGTH // 2\n" ] }, { "cell_type": "markdown", "id": "cell-04", "metadata": {}, "source": [ "## Step 1 — Generate synthetic time-domain data\n", "\n", "Each training sample is a pair:\n", "- **Input** `glitch`: background noise with 1–30 synthetic signal injections (chirps, sine-Gaussians, etc.)\n", "- **Target** `background`: the same noise without any injections\n", "\n", "The model learns to map glitchy strain → clean background." ] }, { "cell_type": "code", "execution_count": null, "id": "cell-05", "metadata": {}, "outputs": [], "source": [ "mean, std_dev = 0, np.sqrt(SAMPLE_RATE / 2) # PyCBC convention: variance = SAMPLE_RATE / 2\n", "\n", "print(\"Generating training noise...\")\n", "train_noise = generate_gaussian_noise(mean, std_dev, N_TRAIN, (LENGTH,), bilby_noise=False)\n", "print(\"Generating validation noise...\")\n", "val_noise = generate_gaussian_noise(mean, std_dev, N_VAL, (LENGTH,), bilby_noise=False)\n", "\n", "print(\"Generating training pairs...\")\n", "glitch_train, bg_train = generate_synthetic_data(train_noise, bilby_noise=False, phase=\"train\")\n", "print(\"Generating validation pairs...\")\n", "glitch_val, bg_val = generate_synthetic_data(val_noise, bilby_noise=False, phase=\"val\")\n", "\n", "print(f\"\\nTrain: {glitch_train.shape} | Val: {glitch_val.shape}\")" ] }, { "cell_type": "markdown", "id": "cell-06", "metadata": {}, "source": [ "## Step 2 — Scale and convert to spectrograms" ] }, { "cell_type": "code", "execution_count": 4, "id": "cell-07", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Spectrogram shape: torch.Size([999, 2, 129, 129]) — (N, 2, freq_bins, time_bins)\n" ] } ], "source": [ "scaler = StandardScaler()\n", "glitch_train_scaled = scaler.fit_transform(glitch_train.reshape(-1, 1)).reshape(glitch_train.shape)\n", "bg_train_scaled = scaler.transform(bg_train.reshape(-1, 1)).reshape(bg_train.shape)\n", "glitch_val_scaled = scaler.transform(glitch_val.reshape(-1, 1)).reshape(glitch_val.shape)\n", "bg_val_scaled = scaler.transform(bg_val.reshape(-1, 1)).reshape(bg_val.shape)\n", "\n", "# Uncomment to save the scaler for use outside this notebook\n", "# import pickle, os\n", "# os.makedirs('/tmp/de_training_tutorial', exist_ok=True)\n", "# with open('/tmp/de_training_tutorial/scaler.pkl', 'wb') as f:\n", "# pickle.dump(scaler, f)\n", "\n", "# Convert to STFT spectrograms (in-memory)\n", "window = torch.hann_window(WIN_LENGTH)\n", "\n", "def to_mag_phase(arrays):\n", " \"\"\"Convert a numpy array (N, time) to a (N, 2, F, T) mag/phase tensor.\"\"\"\n", " t = torch.tensor(arrays, dtype=torch.float32)\n", " stft = torch.stft(t, n_fft=N_FFT, hop_length=HOP_LENGTH, win_length=WIN_LENGTH,\n", " window=window, return_complex=True)\n", " mag = torch.abs(stft)\n", " phase = torch.angle(stft)\n", " return torch.stack([mag, phase], dim=1) # (N, 2, F, T)\n", "\n", "glitch_train_spec = to_mag_phase(glitch_train_scaled)\n", "bg_train_spec = to_mag_phase(bg_train_scaled)\n", "glitch_val_spec = to_mag_phase(glitch_val_scaled)\n", "bg_val_spec = to_mag_phase(bg_val_scaled)\n", "\n", "print(f\"Spectrogram shape: {glitch_train_spec.shape} — (N, 2, freq_bins, time_bins)\")\n", "\n", "# Uncomment to save spectrograms to disk (useful for large datasets or re-use)\n", "# os.makedirs('/tmp/de_training_tutorial/spectrogram_domain', exist_ok=True)\n", "# for name, arr in [\n", "# ('glitch_train_scaled_mag_phase', glitch_train_spec.numpy()),\n", "# ('background_train_scaled_mag_phase', bg_train_spec.numpy()),\n", "# ('glitch_val_scaled_mag_phase', glitch_val_spec.numpy()),\n", "# ('background_val_scaled_mag_phase', bg_val_spec.numpy()),\n", "# ]:\n", "# np.save(f'/tmp/de_training_tutorial/spectrogram_domain/{name}', arr)\n" ] }, { "cell_type": "markdown", "id": "cell-08", "metadata": {}, "source": [ "## Step 3 — Build model and data loaders" ] }, { "cell_type": "code", "execution_count": 5, "id": "cell-09", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model parameters: 7,762,786\n", "Train batches: 32 | Val batches: 7\n", "Spectrogram shape: torch.Size([999, 2, 129, 129]) — (N, 2, freq_bins, time_bins)\n" ] } ], "source": [ "from torch.utils.data import TensorDataset, DataLoader\n", "\n", "# Model architecture\n", "# Original DeepExtractor (arXiv:2501.18423): features=[64, 128, 256, 512] — ~31M parameters.\n", "# Use those to train a model equivalent to the published DeepExtractor.\n", "# Tutorial default: one fewer layer and half the filters for faster training.\n", "model = UNET2D(in_channels=2, out_channels=2, features=[32, 64, 128, 256]).to(DEVICE)\n", "print(f\"Model parameters: {sum(p.numel() for p in model.parameters()):,}\")\n", "\n", "train_ds = TensorDataset(glitch_train_spec, bg_train_spec)\n", "val_ds = TensorDataset(glitch_val_spec, bg_val_spec)\n", "\n", "train_loader = DataLoader(train_ds, batch_size=BATCH_SIZE, shuffle=True)\n", "val_loader = DataLoader(val_ds, batch_size=BATCH_SIZE, shuffle=False)\n", "\n", "print(f\"Train batches: {len(train_loader)} | Val batches: {len(val_loader)}\")\n", "print(f\"Spectrogram shape: {glitch_train_spec.shape} — (N, 2, freq_bins, time_bins)\")\n" ] }, { "cell_type": "markdown", "id": "cell-10", "metadata": {}, "source": [ "## Step 4 — Train\n", "\n", "We train the network for up to `EPOCHS` iterations. For this minimal tutorial configuration\n", "(1000 samples, reduced model), 50 epochs is sufficient to see the loss converge.\n", "To train a model to full convergence, set `EPOCHS` to a large number (e.g. 200) — the learning rate\n", "scheduler and early stopping will halt training automatically once the validation loss stops\n", "improving. For longer runs, we recommend using a CUDA GPU (e.g. Google Colab).\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "cell-11", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:21<00:00, 1.46it/s, loss=2.44]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 2.545411\n", "Epoch 1/50 train=2.80453 val=2.54541 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:14<00:00, 2.13it/s, loss=1.95]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 1.898977\n", "Epoch 2/50 train=2.11057 val=1.89898 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.06it/s, loss=1.87]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 1.739838\n", "Epoch 3/50 train=1.76422 val=1.73984 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.08it/s, loss=1.59]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 1.527682\n", "Epoch 4/50 train=1.58719 val=1.52768 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.08it/s, loss=1.37]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 1.414211\n", "Epoch 5/50 train=1.45410 val=1.41421 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.10it/s, loss=1.31]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 1.315434\n", "Epoch 6/50 train=1.35142 val=1.31543 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.12it/s, loss=1.3] \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 1.250888\n", "Epoch 7/50 train=1.26978 val=1.25089 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.09it/s, loss=1.25]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 1.190232\n", "Epoch 8/50 train=1.20637 val=1.19023 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.10it/s, loss=1.14]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 1.114848\n", "Epoch 9/50 train=1.14198 val=1.11485 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.12it/s, loss=1.01]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 1.045667\n", "Epoch 10/50 train=1.08104 val=1.04567 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.11it/s, loss=1.22] \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 1.002437\n", "Epoch 11/50 train=1.03745 val=1.00244 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.11it/s, loss=0.947]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.969374\n", "Epoch 12/50 train=0.98899 val=0.96937 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.08it/s, loss=0.862]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.923322\n", "Epoch 13/50 train=0.95065 val=0.92332 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.09it/s, 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2.13it/s, loss=0.781]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.635428\n", "Epoch 28/50 train=0.64983 val=0.63543 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.13it/s, loss=0.727]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.627622\n", "Epoch 29/50 train=0.63804 val=0.62762 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.12it/s, loss=0.954]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.618593\n", "Epoch 30/50 train=0.63539 val=0.61859 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.13it/s, loss=0.668]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.611341\n", "Epoch 31/50 train=0.62093 val=0.61134 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.13it/s, loss=0.553]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.602130\n", "Epoch 32/50 train=0.61050 val=0.60213 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.08it/s, loss=0.641]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.595242\n", "Epoch 33/50 train=0.60573 val=0.59524 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.06it/s, loss=0.722]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.591198\n", "Epoch 34/50 train=0.60226 val=0.59120 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.01it/s, loss=0.483]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.586757\n", "Epoch 35/50 train=0.59358 val=0.58676 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.10it/s, loss=0.562]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.579123\n", "Epoch 36/50 train=0.58803 val=0.57912 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.11it/s, loss=0.686]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.574063\n", "Epoch 37/50 train=0.58425 val=0.57406 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.09it/s, loss=0.484]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.571091\n", "Epoch 38/50 train=0.57496 val=0.57109 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.11it/s, loss=0.487]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.565416\n", "Epoch 39/50 train=0.57061 val=0.56542 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.12it/s, loss=0.567]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.561408\n", "Epoch 40/50 train=0.56795 val=0.56141 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.11it/s, loss=0.662]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.557326\n", "Epoch 41/50 train=0.56774 val=0.55733 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.12it/s, loss=0.492]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.555361\n", "Epoch 42/50 train=0.55907 val=0.55536 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.12it/s, loss=0.43] \n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.553943\n", "Epoch 43/50 train=0.55506 val=0.55394 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.10it/s, loss=0.373]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.551764\n", "Epoch 44/50 train=0.55177 val=0.55176 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.11it/s, loss=0.597]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.546904\n", "Epoch 45/50 train=0.55447 val=0.54690 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.10it/s, loss=0.397]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.544676\n", "Epoch 46/50 train=0.54620 val=0.54468 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.10it/s, loss=0.658]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.542234\n", "Epoch 47/50 train=0.55152 val=0.54223 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.11it/s, loss=0.455]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.540582\n", "Epoch 48/50 train=0.54364 val=0.54058 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.11it/s, loss=0.538]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.539683\n", "Epoch 49/50 train=0.54304 val=0.53968 lr=1.0e-04\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Training on batch: 100%|██████████| 32/32 [00:15<00:00, 2.10it/s, loss=0.697]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Validation Loss: 0.537573\n", "Epoch 50/50 train=0.54464 val=0.53757 lr=1.0e-04\n", "\n", "Training complete.\n" ] } ], "source": [ "loss_fn = nn.MSELoss()\n", "optimizer = optim.Adam(model.parameters(), lr=LR)\n", "scheduler = ReduceLROnPlateau(optimizer, mode=\"min\", factor=LR_FACTOR, patience=LR_PATIENCE)\n", "amp_scaler = torch.amp.GradScaler(\"cuda\") if DEVICE == \"cuda\" else torch.amp.GradScaler(\"cpu\")\n", "\n", "train_losses, val_losses = [], []\n", "best_val_loss = float(\"inf\")\n", "early_stopping_counter = 0\n", "\n", "for epoch in range(EPOCHS):\n", " train_loss, _, _ = train_fn(\n", " train_loader, model, \"DeepExtractor_257\", optimizer, loss_fn, amp_scaler, DEVICE\n", " )\n", " val_loss, _, _ = check_accuracy(val_loader, model, \"DeepExtractor_257\", device=DEVICE)\n", "\n", " train_losses.append(train_loss)\n", " val_losses.append(val_loss)\n", " scheduler.step(val_loss)\n", "\n", " current_lr = optimizer.param_groups[0]['lr']\n", " print(f\"Epoch {epoch+1:>3}/{EPOCHS} train={train_loss:.5f} val={val_loss:.5f} lr={current_lr:.1e}\")\n", "\n", " if val_loss < best_val_loss:\n", " best_val_loss = val_loss\n", " early_stopping_counter = 0\n", " else:\n", " early_stopping_counter += 1\n", " if early_stopping_counter >= EARLY_STOPPING_PATIENCE:\n", " print(f\"\\nEarly stopping at epoch {epoch+1} (no improvement for {EARLY_STOPPING_PATIENCE} epochs).\")\n", " break\n", "\n", "print(\"\\nTraining complete.\")\n" ] }, { "cell_type": "markdown", "id": "cell-12", "metadata": {}, "source": [ "## Step 5 — Plot losses" ] }, { "cell_type": "code", "execution_count": 7, "id": "cell-13", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "epochs_ran = range(1, len(train_losses) + 1)\n", "\n", "fig, ax = plt.subplots(figsize=(8, 4))\n", "ax.plot(epochs_ran, train_losses, label=\"Train\", color=\"C0\")\n", "ax.plot(epochs_ran, val_losses, label=\"Validation\", color=\"C1\")\n", "ax.set_xlabel(\"Epoch\")\n", "ax.set_ylabel(\"MSE Loss\")\n", "ax.set_title(\"Training and Validation Loss\")\n", "ax.legend()\n", "ax.grid(True)\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "markdown", "id": "cell-14", "metadata": {}, "source": [ "## Step 6 — Test on sine-Gaussian injections\n", "\n", "We generate fresh test examples — PyCBC (numpy) noise with a sine-Gaussian injected at a range of SNRs —\n", "and run them through the trained model.\n", "The model was never trained on these specific examples.\n", "We use three different test examples at three different SNRs, reporting the SNR and mismatch ($\\mathcal{M}$) above each plot. \n", "Intuitively, the model better recovers louder glitches than quieter ones. \n", "The reconstructions below feature high-frequency artifacts as the model training did not fully converge, and it is a reduced architecture compared to the published version. \n", "Improved performance can be achieved by training this model until convergence or by modifying the layers of DeepExtractor's U-Net to the published architecture, and increasing the resolution of the STFT spectrograms (please see above)." ] }, { "cell_type": "code", "execution_count": 8, "id": "cell-15", "metadata": {}, "outputs": [], "source": [ "def reconstruct(noisy_signal, model, scaler, device, n_fft, hop_length, win_length):\n", " \"\"\"Scale → STFT → U-Net → iSTFT → unscale → subtract background.\"\"\"\n", " # Scale\n", " scaled = scaler.transform(noisy_signal.reshape(-1, 1)).reshape(noisy_signal.shape)\n", "\n", " # STFT\n", " window = torch.hann_window(win_length)\n", " t = torch.tensor(scaled, dtype=torch.float32).unsqueeze(0) # (1, time)\n", " stft = torch.stft(t, n_fft=n_fft, hop_length=hop_length, win_length=win_length,\n", " window=window, return_complex=True)\n", " mag = torch.abs(stft)\n", " phase = torch.angle(stft)\n", " spec = torch.stack([mag, phase], dim=1) # (1, 2, F, T)\n", "\n", " # U-Net inference\n", " model.eval()\n", " with torch.no_grad():\n", " bg_spec = model(spec.to(device)).cpu() # predicted background spectrogram\n", "\n", " # iSTFT\n", " bg_mag = bg_spec[:, 0, :, :]\n", " bg_phase = bg_spec[:, 1, :, :]\n", " bg_complex = bg_mag * torch.exp(1j * bg_phase)\n", " bg_td = torch.istft(bg_complex, n_fft=n_fft, hop_length=hop_length,\n", " win_length=win_length, window=window,\n", " length=noisy_signal.shape[-1])\n", "\n", " # Unscale and subtract background to recover signal\n", " bg_unscaled = scaler.inverse_transform(bg_td.numpy().reshape(-1, 1)).reshape(-1)\n", " noisy_unscaled = noisy_signal.copy()\n", " reconstruction = noisy_unscaled - bg_unscaled\n", " return reconstruction" ] }, { "cell_type": "code", "execution_count": 9, "id": "cell-16", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "<>:38: SyntaxWarning: invalid escape sequence '\\%'\n", "<>:38: SyntaxWarning: invalid escape sequence '\\%'\n", "/var/folders/xj/6sk96vdn15385fpjn9nd1rcw0000gp/T/ipykernel_22077/3874219395.py:38: SyntaxWarning: invalid escape sequence '\\%'\n", " f\"$\\\\mathcal{{M}} = {mismatch*100:.1f} \\% $\"\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Generating pycbc noise...\n", "Generating pycbc noise...\n", "Generating pycbc noise...\n" ] }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "T_INJ = T / 2\n", "SNR_VALUES = [15, 30, 100]\n", "\n", "def overlap(a, b):\n", " \"\"\"Normalised time-domain overlap (match) between two real signals.\n", " Equivalent to the PyCBC match on whitened data (flat PSD).\"\"\"\n", " return np.dot(a, b) / np.sqrt(np.dot(a, a) * np.dot(b, b))\n", "\n", "fig, axes = plt.subplots(len(SNR_VALUES), 1, figsize=(12, 4 * len(SNR_VALUES)))\n", "t_axis = np.linspace(0, T, LENGTH)\n", "\n", "for ax, snr in zip(axes, SNR_VALUES):\n", " noise = generate_gaussian_noise(mean, std_dev, 1, (LENGTH,), bilby_noise=False)[0]\n", " \n", " # We set freq_max=256 when generating the sine-Gaussians for visualization purposes. This can be increased to the Nyquist frequency (i.e. freq_max=2048).\n", " _, wavelet = generate_sine_gaussian(duration=0.5, freq_max=256)\n", " wavelet = wavelet - np.mean(wavelet)\n", " wavelet = whitened_snr_scaling(wavelet, snr=snr)\n", "\n", " len_glitch = len(wavelet)\n", " id_start = int(T_INJ * SAMPLE_RATE) - len_glitch // 2\n", " noisy = noise.copy()\n", " noisy[id_start : id_start + len_glitch] += wavelet\n", "\n", " injected = np.zeros(LENGTH)\n", " injected[id_start : id_start + len_glitch] = wavelet\n", "\n", " reconstructed = reconstruct(noisy, model, scaler, DEVICE, N_FFT, HOP_LENGTH, WIN_LENGTH)\n", "\n", " match = overlap(injected, reconstructed)\n", " mismatch = 1.0 - match\n", "\n", " ax.plot(t_axis, noisy, color=\"gray\", lw=0.8, alpha=0.4, label=\"Noise + Glitch\")\n", " ax.plot(t_axis, reconstructed, color=\"C0\", lw=1.5, label=\"Reconstructed\")\n", " ax.plot(t_axis, injected, color=\"black\", lw=1.5, alpha=0.6, linestyle=\"--\", label=\"Injected (ground truth)\")\n", " ax.set_title(\n", " f\"Sine-Gaussian SNR={snr} | \"\n", " f\"$\\\\mathcal{{M}} = {mismatch*100:.1f} \\% $\"\n", " )\n", " ax.set_xlabel(\"Time (s)\")\n", " ax.set_ylabel(\"Amplitude\")\n", " ax.legend(loc=\"upper right\")\n", " ax.grid(True)\n", "\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "id": "128ece8f", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "deepextractor-test", "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": "3.11.15" } }, "nbformat": 4, "nbformat_minor": 5 }