{ "cells": [ { "cell_type": "markdown", "id": "0bd4c865", "metadata": {}, "source": "# Exploring the CRCNS AA1 and AA2 datasets with deepSTRF\n\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/urancon/deepSTRF/blob/develop/examples/crcns_aa_tutorial.ipynb)\n\nThis notebook walks through the deepSTRF dataset API on two closely related\nauditory neurophysiology datasets:\n\n- **[CRCNS AA1](https://crcns.org/data-sets/aa/aa-1/about)** (Theunissen et al.,\n 2009) — single-unit spike trains from the Field-L and MLd regions of\n anesthetized zebra finches, responding to conspecific songs and flat ripples.\n- **[CRCNS AA2](https://crcns.org/data-sets/aa/aa-2/about)** (Gill et al., 2006 /\n Amin et al., 2010) — same species, larger cohort (~500 neurons across Field-L,\n MLd, OV, CM), three stim classes (conspecific, flat ripples, song ripples).\n\nBy the end, you will have seen:\n\n1. How to **instantiate** a deepSTRF dataset.\n2. How the data are **stored internally** (list-of-lists, NaN-sentinel\n missingness) — see\n [`data_paradigm.md`](../docs/_source/md/data_paradigm.md) for the full\n design rationale.\n3. How to **visualize** a stimulus spectrogram and its recorded PSTH.\n4. How to use the **neuron selection API** (`select_neuron`,\n `select_pop_by_nrn_attr`, …).\n5. How to iterate the dataset with a **PyTorch `DataLoader`** via the\n batch-collate function.\n\n**Data:** the AA1 / AA2 archives are auto-downloaded from crcns.org on\nfirst use (`download=True` in the constructor). You'll need a free CRCNS\naccount — see the setup section below.\n" }, { "cell_type": "markdown", "id": "aeb0b654", "metadata": {}, "source": "## Setup — Google Colab\n\nIf you're running on Google Colab, the cell below installs deepSTRF\nfrom source. On a local install (`pip install -e .`) it's a no-op.\n\n**Note on data**: AA1 and AA2 are authenticated CRCNS datasets. To\nauto-download them, set `$CRCNS_USERNAME` and `$CRCNS_PASSWORD` (free\naccount at https://crcns.org/) before running the dataset cells. On\na local machine that already has the data extracted, it's picked up\nfrom the cache automatically." }, { "cell_type": "code", "execution_count": null, "id": "fc49cf8b", "metadata": {}, "outputs": [], "source": [ "import sys\n", "if 'google.colab' in sys.modules:\n", " !pip install -q git+https://github.com/urancon/deepSTRF.git\n", " print(\"deepSTRF installed from GitHub.\")\n", "else:\n", " print(\"Local environment — assuming deepSTRF is already importable.\")\n" ] }, { "cell_type": "markdown", "id": "79d775c2", "metadata": {}, "source": [ "## Imports" ] }, { "cell_type": "code", "execution_count": null, "id": "98e57a15", "metadata": { "execution": { "iopub.execute_input": "2026-04-25T10:46:46.753613Z", "iopub.status.busy": "2026-04-25T10:46:46.752867Z", "iopub.status.idle": "2026-04-25T10:46:50.335720Z", "shell.execute_reply": "2026-04-25T10:46:50.334407Z" } }, "outputs": [], "source": "%matplotlib inline\nimport matplotlib.pyplot as plt\nimport torch\nfrom torch.utils.data import DataLoader\n\nfrom deepSTRF.datasets.audio.crcns_aa1 import CRCNSAA1Dataset\nfrom deepSTRF.datasets.audio.crcns_aa2 import CRCNSAA2Dataset\nfrom deepSTRF.utils.data import neural_collate\n\n# Bin width in ms. Typical choices: 1, 5, 10.\nDT_MS = 5\n" }, { "cell_type": "markdown", "id": "cc6d5476", "metadata": {}, "source": [ "## 1. Instantiating AA1\n", "\n", "The constructor takes a `path` to the data folder, plus dataset-specific\n", "selection arguments (recording area, stimulus type, animal, bin width, …).\n", "All stimuli and responses are preprocessed in the constructor so the object\n", "is ready for iteration immediately.\n" ] }, { "cell_type": "code", "execution_count": null, "id": "2d19abe3", "metadata": { "execution": { "iopub.execute_input": "2026-04-25T10:46:50.340393Z", "iopub.status.busy": "2026-04-25T10:46:50.339866Z", "iopub.status.idle": "2026-04-25T10:47:01.449591Z", "shell.execute_reply": "2026-04-25T10:47:01.448777Z" } }, "outputs": [], "source": "aa1 = CRCNSAA1Dataset(\n download=True,\n areas=(\"Field_L\", \"MLd\"),\n stimuli=(\"conspecific\", \"flatrip\"),\n dt_ms=DT_MS,\n)\naa1\n" }, { "cell_type": "markdown", "id": "b59dc6c9", "metadata": {}, "source": [ "## 2. How data are stored\n", "\n", "deepSTRF datasets are **triply ragged** — stimulus duration varies, repeat count\n", "varies per (stim, neuron), and coverage is sparse (not every neuron heard every\n", "stim). They are stored as Python lists of tensors rather than stacked tensors,\n", "with NaN as the single channel for encoding missingness.\n", "\n", "Core attributes populated by every `NeuralDataset` subclass:\n", "\n", "| attribute | shape / structure |\n", "|-----------------------|--------------------------------------------------------------------------------|\n", "| `self.stims` | length-S list; each element is a `(1, F, T_s)` mel-spectrogram (T varies) |\n", "| `self.responses` | length-S list of length-N lists; `responses[s][n]` is `(R_{s,n}, T_s)` or `(1, 1)` NaN |\n", "| `self.stim_meta` | length-S list of per-stim dicts, e.g. `{\"name\", \"type\"}` |\n", "| `self.nrn_meta`| length-N list of per-neuron dicts, e.g. `{\"cell_id\", \"animal_id\", \"area\"}` |\n", "| `self.nrn_masks` | derived `@property`: `(S, N)` bool tensor — True iff (stim, neuron) has data |\n", "\n", "Let's confirm all the shapes are consistent with the paradigm.\n" ] }, { "cell_type": "code", "execution_count": 3, "id": "1de90708", "metadata": { "execution": { "iopub.execute_input": "2026-04-25T10:47:01.452317Z", "iopub.status.busy": "2026-04-25T10:47:01.451933Z", "iopub.status.idle": "2026-04-25T10:47:01.728112Z", "shell.execute_reply": "2026-04-25T10:47:01.726557Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "S (stimuli) = 30\n", "N (neurons) = 100\n", "dt = 5 ms\n", "\n", "stims[0].shape = (1, 32, 389) (1, F, T_0)\n", "stim T range = [330, 501] bins\n", "\n", "responses[0][0] shape = (10, 389)\n", "stim_meta[0] = {'name': '058767E725C83836F405A97FD7D1E751.wav', 'type': 'conspecific'}\n", "nrn_meta[0] = {'cell_id': 'gg0304_10_B', 'animal_id': 'gg0304', 'area': 'Field_L'}\n", "\n", "nrn_masks.shape = (30, 100), dtype = torch.bool\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "nrn_masks valid = 2960 / 3000 (98.7%)\n" ] } ], "source": [ "print(f\"S (stimuli) = {aa1.get_S()}\")\n", "print(f\"N (neurons) = {aa1.get_N()}\")\n", "print(f\"dt = {aa1.dt} ms\")\n", "print()\n", "print(f\"stims[0].shape = {tuple(aa1.stims[0].shape)} (1, F, T_0)\")\n", "print(f\"stim T range = [{min(s.shape[-1] for s in aa1.stims)}, \"\n", " f\"{max(s.shape[-1] for s in aa1.stims)}] bins\")\n", "print()\n", "print(f\"responses[0][0] shape = {tuple(aa1.responses[0][0].shape)}\")\n", "print(f\"stim_meta[0] = {aa1.stim_meta[0]}\")\n", "print(f\"nrn_meta[0] = {aa1.nrn_meta[0]}\")\n", "print()\n", "print(f\"nrn_masks.shape = {tuple(aa1.nrn_masks.shape)}, dtype = {aa1.nrn_masks.dtype}\")\n", "print(f\"nrn_masks valid = {int(aa1.nrn_masks.sum())} / {aa1.nrn_masks.numel()} \"\n", " f\"({100 * aa1.nrn_masks.float().mean().item():.1f}%)\")\n" ] }, { "cell_type": "markdown", "id": "d17e6ce2", "metadata": {}, "source": [ "## 3. Visualizing a stimulus\n", "\n", "Stimuli are mel-spectrograms of shape `(1, F, T)`, stored as float tensors.\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "111758b7", "metadata": { "execution": { "iopub.execute_input": "2026-04-25T10:47:01.730556Z", "iopub.status.busy": "2026-04-25T10:47:01.730124Z", "iopub.status.idle": "2026-04-25T10:47:02.658524Z", "shell.execute_reply": "2026-04-25T10:47:02.657202Z" } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "stim_idx = 0\n", "stim = aa1.stims[stim_idx].squeeze(0) # (F, T)\n", "meta = aa1.stim_meta[stim_idx]\n", "fig, ax = plt.subplots(figsize=(8, 3))\n", "im = ax.imshow(stim.numpy(), aspect=\"auto\", origin=\"lower\", cmap=\"magma\")\n", "ax.set_xlabel(f\"Time (bins of {aa1.dt} ms)\")\n", "ax.set_ylabel(\"Mel-frequency band\")\n", "ax.set_title(f\"Stim {stim_idx}: {meta['type']} — {meta['name']}\")\n", "fig.colorbar(im, ax=ax, label=\"compressed power\")\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "markdown", "id": "a11d9889", "metadata": {}, "source": [ "## 4. Visualizing a response\n", "\n", "Responses are spike-count tensors per (stim, neuron) pair, shaped `(R, T)` —\n", "one row per repeat. The trial-averaged PSTH is `response.mean(dim=0)`.\n", "\n", "Note: missing (stim, neuron) pairs are `(1, 1)` NaN tensors, so we pick a\n", "(stim, neuron) pair that `nrn_masks` confirms as real data.\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "97ac208d", "metadata": { "execution": { "iopub.execute_input": "2026-04-25T10:47:02.660683Z", "iopub.status.busy": "2026-04-25T10:47:02.660469Z", "iopub.status.idle": "2026-04-25T10:47:02.986989Z", "shell.execute_reply": "2026-04-25T10:47:02.986053Z" } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# find a (s, n) pair that has real data\n", "valid_pairs = aa1.nrn_masks.nonzero()\n", "stim_idx, neuron_idx = valid_pairs[0].tolist()\n", "\n", "spikes = aa1.responses[stim_idx][neuron_idx] # (R, T)\n", "psth = spikes.mean(dim=0) # (T,)\n", "time_ms = torch.arange(spikes.shape[-1]) * aa1.dt\n", "\n", "nrn = aa1.nrn_meta[neuron_idx]\n", "stim_m = aa1.stim_meta[stim_idx]\n", "\n", "fig, (ax0, ax1) = plt.subplots(2, 1, figsize=(8, 4), sharex=True)\n", "ax0.imshow(spikes.numpy(), aspect=\"auto\", cmap=\"Greys\",\n", " extent=[0, float(time_ms[-1]), 0, spikes.shape[0]])\n", "ax0.set_ylabel(\"Repeat\")\n", "ax0.set_title(f\"Neuron {neuron_idx} ({nrn['area']} / {nrn['cell_id']}) \"\n", " f\"→ stim {stim_idx} ({stim_m['type']})\")\n", "ax1.plot(time_ms, psth.numpy(), lw=1)\n", "ax1.set_xlabel(\"Time (ms)\")\n", "ax1.set_ylabel(\"PSTH (smoothed spike count)\")\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "markdown", "id": "7a0c1fd2", "metadata": {}, "source": [ "## 5. Coverage: the `nrn_masks` tensor\n", "\n", "`dataset.nrn_masks` is a derived `(S, N)` bool tensor, `True` iff neuron *n*\n", "has real data for stimulus *s*. It is computed on the fly from the NaN\n", "sentinels — the single source of truth is `self.responses`. A heatmap\n", "exposes the sparse coverage pattern.\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "7ca42cdc", "metadata": { "execution": { "iopub.execute_input": "2026-04-25T10:47:02.989129Z", "iopub.status.busy": "2026-04-25T10:47:02.988917Z", "iopub.status.idle": "2026-04-25T10:47:03.234441Z", "shell.execute_reply": "2026-04-25T10:47:03.233153Z" } }, "outputs": [ { "data": { "image/png": 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eNBUqVDANGza0lm3fvt1IMr169bKpGxkZaSSZIUOGWMs6dOhgAgICzPnz523qtmzZ0nh5eaU634Nw6NAhI8m4ubmZ48ePW8u3bNliJJnevXtby4YMGWLuvLynFXN4eLjN3+PSpUvGw8PDhISEmOvXr9vUTWkDxhhTv359U758eWOMMfPmzTNOTk6mY8eOJikpKcPXkRJbRo8SJUpkeKzXXnvNeHt7pyr/z3/+Y40vPR988IGRZA4dOpRqW4kSJWz+70ybNs1IMuHh4TbvQ2hoqLFYLKZLly7WssTERFO0aFFTv379DONPS8r70759e5vyl156yea1Hj582Dg6Opr33nvPpt5vv/1m8uTJY1N+5+tJUb9+fZs4f/zxRyPJlCpVyqa93Lx50/j6+poKFSrYtIulS5caSWbw4MHWsrZt2xpJ5p133rE5V5UqVUy1atVSxbBp0yYjycyZMyedd+QfKX+DatWqmZs3b1rLR40aZSSZRYsWWcvSauudO3c2efPmNTdu3LCJ9fZ2lvJ/zNPT05w9e/au8aSQZJydnc3+/futZb/++quRZMaPH3/XmDZv3mwkmS+//NJaVrlyZfP8889n6ty3S3l/6tataxITE63lly9fNvnz5zcdO3a0qX/69Gnj5eVlU16vXj3j4eFhjhw5YlP39jbftGlT4+zsbA4cOGAtO3nypPHw8DD16tXLMJ6UtvTEE0+YhIQEa/nUqVONJJv2mNnPh127dhlJpmvXrjb1WrduneranpaUz7VvvvnGWnb16lVTunRpI8n8+OOP1vK0/o7R0dHGYrHYvG9RUVGprsHpHSOtz6us+N///mckmcuXL9uUjx492khK9f4NGDDASDIvvPCCtSwxMdF069bNODk5Wa/Bjo6OZtKkSfcUU0REhHFxcTEXL160Kd+9e7cpWrSo9RwREREmKSnJHDx40Li5uZnNmzdn6viPPfaYefbZZ+8pNiCnMLwceMBiYmLk5+dnnfgpZUbyr7/+Os3hlzExMapevbp1orWUoYEZDUnPqnnz5qly5cpp/nKc0oO0fPly+fv729yj5eTkpB49eujKlStat26dJKlhw4YqVKiQ5syZY6138eJFrVy50mb29W+//VZly5ZVcHCwzp8/b32kTKr0448/2sRRv359lStXLlV8tw9/u3jxouLi4vTkk09qx44d1vKU4Z5du3a12bd79+42z40xmjdvnl588UUZY2ziCg8PV1xcnM1xH7SmTZuqSJEi1uc1a9ZUSEhIhksv3f4excXF6fz586pfv74OHjyouLg4SdLKlSt1+fJlDRgwwObeQElp3rYwe/ZstWjRQp07d9aUKVMyNflYmzZttHLlygwfmWnfFy5cSLM3PH/+/Dp+/Li2bt2a4TGyokOHDjbvQ0hIiIwx6tChg7XM0dFR1atX18GDB+/rXF26dLF5/uSTT+rChQvWod7z589XcnKymjdvbtNG/f39VaZMmVT/d7Kibdu2Nu1l27ZtOnv2rLp27WrTLp5//nkFBwdr2bJlmYo/rfck5e93+y0sd9OpUyeb++3ffPNN5cmTx6b93x775cuXdf78eT355JO6du2a9u7dm+E5IiIiMhz1cLuwsDAFBQVZn1eqVEmenp42r/f2mG7duqULFy6odOnSyp8/v831JH/+/Prjjz+0b9++TJ//dh07drQZabJy5UpdunRJrVq1smknjo6OCgkJsbaTc+fOaf369Wrfvr2KFy9uc8yUNp+UlKQffvhBTZs2ValSpazbAwIC1Lp1a23YsMHaPtOLJ6UtdenSxaYHNjIyUl5eXjb7ZvbzIeVv36NHD5v9Mzsiafny5QoICNDLL79sLcubN686deqUqu7tf8erV6/q/Pnzql27towx2rlzZ6bOl5nPq6y4cOGC8uTJk2pIduvWreXl5aX27dtr5cqVOnz4sKZOnaqJEydKks2QeEdHRwUFBSk8PFwzZszQnDlz9OKLL6p79+6pRpxlJD4+XsuWLdNzzz2XarRNxYoVtW/fPm3dulX79u3T3Llz5eDgoL59+yoiIkK1atXS/PnzVblyZQUGBuqdd95J89aTAgUKZPqaATwsGF4OPEBJSUn6+uuv9dRTT9kshxESEqLRo0dr9erVNjN9Xrp0ScuXL1e3bt20f/9+a3mdOnU0b948/fXXX3rssceyJbYDBw4oIiLirnWOHDmiMmXKpEquypYta90uSXny5FFERIRmzZqlhIQEubi4aP78+bp165ZN0r1v3z7t2bMn3S+4t0/0IinN2Uylf4Y3Dx8+XLt27bK5D+/2BOnIkSNycHBIdYw7Z40/d+6cLl26pKlTp2rq1KmZiut2f//99z1PvFSwYMFUQwHvVKZMmVRljz32mL755pu77rdx40YNGTJEmzdvTjW8Oy4uTl5eXjpw4IAkZWqY76FDh/Taa6/plVde0fjx4zOsn6JUqVI2X9jvV1pfyN5++22tWrVKNWvWVOnSpdW4cWO1bt1aderUua9z3ZmMpCQJtw+JTSm/8z7j+z1XSnJ68eJFeXp6at++fTLGpNkeJN3XRHB3/h9J+X/9+OOPp6obHBysDRs22JS5urqm+j9doECBNN+TlL9fZueiuPP1uru7KyAgwObe6D/++EP/+9//tGbNmlRJYMoPTHeT3nUmPXf+raTUr/f69euKjo7WtGnTdOLECZt2e3tM77zzjv7zn//oscceU4UKFfTMM8/o9ddfV6VKlTIVy52xpyTv6c0O7+npKUnWHwju9n//3LlzunbtWprtoGzZskpOTtaxY8dUvnz5dONJaUt3/h2dnJxSXRcy+/mQcm2//YcPKe32mpYjR46odOnSqdpgWvsfPXpUgwcP1uLFi1O158y0LSlzn1fZwd/fX4sXL9brr79u/V7h6emp8ePHq23btjZJ+ogRI/Txxx9r37591vLmzZvrqaeeUlRUlF544QXlyZO5lGHevHm6ceNGqqHlKVxdXVW9enXr8zVr1uiHH35QbGysYmNj1bJlS02ZMkUlS5ZUq1atVKxYsVRzxBhjsv39AuyNpBt4gNasWaNTp07p66+/1tdff51qe0xMjE3S/e233yohIUGjR4/W6NGj06w/bNgwu8Z8r1I+OFesWKGmTZvqm2++UXBwsCpXrmytk5ycrIoVK2rMmDFpHuPOZCatCV1++uknNWnSRPXq1dPEiRMVEBAgJycnTZs2LcPJv9KSMlPza6+9prZt26ZZ525fgJs1a2bt8c+qH3/80WZiq+xy4MABNWrUSMHBwRozZoyKFSsmZ2dnLV++XB999NE9zU4dEBCggIAALV++XNu2bbP5EnU3V65cydSss46Ojhn2Nnp7e6eZyJUtW1axsbFaunSpvvvuO82bN08TJ07U4MGD7+v/S3r3qqdVntaPAdlxrpTjJicny2KxaMWKFWnWvf0LdXpfTpOSktLc914mTrrd3e7pv1PK3y/lvvr7denSJdWvX1+enp565513FBQUJFdXV+3YsUNvv/12ptp6Vl9/Rn8r6Z8RNdOmTVOvXr0UGhoqLy8vWSwWtWzZ0iamevXq6cCBA1q0aJF++OEHffbZZ/roo480efJkvfHGG1mOPeXYM2fOTHMOkMwmUvfqftpSVj8f7C0pKUlPP/20/v77b7399tsKDg5Wvnz5dOLECUVGRmaqbWX355X0z3UwMTExzaVE69Wrp4MHD+q3337T1atXVblyZZ08eVKSbH6wnzhxoho2bJiqt7xJkybq06ePDh8+fNdlTW8XExMjLy8vvfDCCxnWTUpKUs+ePTVgwAAVKVJE7777rmrXrm1Nsjt37qyYmJhUSffFixfT/cEReFiRdAMPUExMjHx9fa0zm95u/vz5WrBggSZPnmz9ohITE6MKFSpoyJAhqepPmTJFs2bNyrakOygoKMNZsEuUKKHdu3crOTnZprc7ZchmiRIlrGX16tVTQECA5syZo7p162rNmjWpZsENCgrSr7/+qkaNGt3zr9bz5s2Tq6urvv/+e5vlf6ZNm5Yq9uTkZB06dMjmw/r2EQSSrLPfJiUlpTkrdkZGjx59z72ct/8gkZ60hp3+9ddfNrMw32nJkiVKSEjQ4sWLbXrl7hyCnNJT9Pvvv2f4BcvV1VVLly5Vw4YN9cwzz2jdunU2PVzp+fDDDzPVZkuUKJFqZuc7BQcHKyYmxtpTf7t8+fKpRYsWatGihW7evKlmzZrpvffe08CBA+Xq6prre0mCgoJkjFFgYGCGo10KFCigS5cupSo/cuRIpkYdpPy/jo2NTdVjGhsba/P/PqtSRvykjJbJyL59+2zWZL9y5YpOnTql5557TtI/M7BfuHBB8+fPV7169VKdJ6fMnTtXbdu2tfnx9MaNG2n+XVJWf2jXrp2uXLmievXqaejQoZlKuu+U8n/a19f3rtezlHZwt88AHx8f5c2bV7Gxsam27d27Vw4ODhkmwiltZd++fTZt6datWzp06JDNNTCznw8p1/YDBw7Y9E6nFWd6+//++++pek/v3P+3337TX3/9pRkzZthMkpjWLNrpxZvZz6usCA4OlvRPG0/rB2FHR0c98cQT1uerVq2SJJv2cObMmTRvb7t165YkZXpFilOnTunHH39UZGRkppYtnTRpki5fvmxd0eTkyZMqXLiwdXvhwoVTrZCQmJioY8eOqUmTJpmKCXhYcE838IBcv35d8+fP1wsvvKCXX3451aNbt266fPmyFi9eLEk6duyY1q9fr+bNm6dZv127dtq/f7+2bNmSLfFFRETo119/1YIFC1JtS+mxee6553T69Gmbe7UTExM1fvx4ubu7q379+tZyBwcHvfzyy1qyZIlmzpypxMREm6Hl0j/D106cOGGdvfTO9ysz67o6OjrKYrHYfGE4fPhwqvvQwsPDJcl6P1uKO4dGOzo6KiIiQvPmzUvzC+i5c+fuGk+1atUUFhZ2T4+MZuuW/pkB/vYvIb/88ou2bNmiZ599Nt19Unri7hzSeucXvcaNG8vDw0PR0dGp1kBPq+fWy8tL33//vXx9ffX0009bh6ffTXbe0x0aGipjjLZv325TfuHCBZvnzs7OKleunIwx1i+R+fLlk6Q0k57coFmzZnJ0dNSwYcNS/W2MMTbvQVBQkH7++Web2x6WLl2aammx9FSvXl2+vr6aPHmyzXDYFStWaM+ePfc043KK7du3y8vLK1M/2Ej/LDWV8jeU/vnSnpiYaG3/abX1mzdvpvp//6A5Ojqm+juNHz8+VaJzZ9t1d3dX6dKl01y+KjPCw8Pl6emp999/3+Z9S5FyPfPx8VG9evX0xRdf6OjRozZ1UuJ2dHRU48aNtWjRIpsfxM6cOaNZs2apbt261uHq6alevbp8fHw0efJkm/Y4ffr0VP8XM/v5kPK3HzdunE2dsWPH3jWWFM8995xOnjxps2zXtWvXUt1elFbbMsbo448/TnXM9K4vmf28yorQ0FBJ/9wvn5Fz585p5MiRqlSpkk3S/dhjj2nlypU27S8pKUnffPONPDw8bIbuHzhwIN1r/ddff63k5OR0h5bf7u+//9aQIUP0wQcfWOeK8PPzs5l3Yc+ePalGaPz555+6ceOGateuneE5gIcJPd3AA7J48WJdvnw53V9na9WqJR8fH8XExKhFixaaNWuWjDHp1n/uueeUJ08excTEWJdpWbJkiX799VdJ//xCvXv3bg0fPlzSP8PE7jYs+q233tLcuXP1yiuvqH379qpWrZr+/vtvLV68WJMnT1blypXVqVMnTZkyRZGRkdq+fbtKliypuXPnauPGjRo7dmyqoW0tWrTQ+PHjNWTIEFWsWDFVb9brr7+ub775Rl26dNGPP/6oOnXqKCkpSXv37tU333yj77//PsNhy88//7zGjBmjZ555Rq1bt9bZs2f1ySefqHTp0tq9e7e1XrVq1RQREaGxY8fqwoUL1iXD/vrrL0m2PRMjRozQjz/+qJCQEHXs2FHlypXT33//rR07dmjVqlX6+++/7xqTPZUuXVp169bVm2++qYSEBI0dO1be3t7q379/uvs0btxYzs7OevHFF9W5c2dduXJFn376qXx9fXXq1ClrPU9PT3300Ud64403VKNGDbVu3VoFChTQr7/+qmvXrtmsx56iUKFCWrlyperWrauwsDBt2LDBZqK3O2XnPd1169aVt7e3Vq1aZdNr1rhxY/n7+6tOnTry8/PTnj17NGHCBD3//PPWNlqtWjVJ0v/93/+pZcuWcnJy0osvvmj9spzdIiMjNWPGDB06dOiuoxIyKygoSMOHD9fAgQN1+PBhNW3aVB4eHjp06JAWLFigTp06WXuP3njjDc2dO1fPPPOMmjdvrgMHDuirr75KdQ9sepycnDRy5Ei1a9dO9evXV6tWraxLhpUsWVK9e/e+59excuVKvfjii5keeXDz5k01atRIzZs3V2xsrCZOnKi6detar5O1a9dWgQIF1LZtW/Xo0UMWi0UzZ8687+H+9+uFF17QzJkz5eXlpXLlymnz5s1atWqVdUmxFOXKlVODBg1UrVo1FSxYUNu2bdPcuXPVrVu3ezqvp6enJk2apNdff11Vq1ZVy5Yt5ePjo6NHj2rZsmWqU6eOJkyYIOmfpLVu3bqqWrWqOnXqpMDAQB0+fFjLli3Trl27JEnDhw+3/n/v2rWr8uTJoylTpighIUGjRo3KMB4nJycNHz5cnTt3VsOGDdWiRQsdOnRI06ZNS3VdyOznwxNPPKFWrVpp4sSJiouLU+3atbV69epUo5jS07FjR02YMEFt2rTR9u3bFRAQoJkzZ1qX1koRHBysoKAg9evXTydOnJCnp6fmzZuX5simlOtLjx49FB4eLkdHR7Vs2TLTn1dZUapUKVWoUEGrVq1S+/btbbbVr19foaGhKl26tE6fPq2pU6fqypUrWrp0qc1otQEDBui1115TSEiIOnXqJDc3N82ePVvbt2/X8OHDbeaIaNSokSSlORIpJiZGhQsXztRtUoMGDVLFihX1yiuvWMsiIiL0zjvv6M0331SJEiU0ZcqUVLcXrFy5Unnz5s3UEnrAQ+WBzJEOwLz44ovG1dXVXL16Nd06kZGRxsnJyZw/f95UrFjRFC9e/K7HbNCggfH19TW3bt0yxvz/5XrSekybNi3DGC9cuGC6detmihQpYpydnU3RokVN27ZtbZbOOnPmjGnXrp0pVKiQcXZ2NhUrVkz32MnJyaZYsWJGkhk+fHiadW7evGlGjhxpypcvb1xcXEyBAgVMtWrVzLBhw0xcXJy1niQTFRWV5jE+//xzU6ZMGePi4mKCg4PNtGnT0lw26+rVqyYqKsoULFjQuLu7m6ZNm5rY2FgjyYwYMcKm7pkzZ0xUVJQpVqyYcXJyMv7+/qZRo0Zm6tSpGb6P9pCynNEHH3xgRo8ebYoVK2ZcXFzMk08+aX799Vebumm99sWLF5tKlSoZV1dXU7JkSTNy5EjzxRdfpLls1uLFi03t2rWNm5ub8fT0NDVr1jSzZ8+2br99ybAU+/fvNwEBAaZs2bLm3Llz2fvi76JHjx6mdOnSNmVTpkwx9erVM97e3sbFxcUEBQWZt956y6Y9GWPMu+++a4oUKWIcHBxs3of0lgzbunWrzf4p7/Odr7dt27YmX758NmURERHGzc0t1RI6d0rvmCkx3Pm3mjdvnqlbt67Jly+fyZcvnwkODjZRUVEmNjbWpt7o0aNNkSJFjIuLi6lTp47Ztm1bukuGffvtt2nGNmfOHFOlShXj4uJiChYsaF599VWb5evSe+23v67b7dmzx0gyq1atuut7cvvrX7dunenUqZMpUKCAcXd3N6+++qq5cOGCTd2NGzeaWrVqGTc3N1O4cGHTv39/6zKGty//lN6SYR988EGG8aRI77p0Zxu6ePGi9brp7u5uwsPDzd69e1PVGz58uKlZs6bJnz+/cXNzM8HBwea9996zWSbtbu/PnW00xY8//mjCw8ONl5eXcXV1NUFBQSYyMtJs27bNpt7vv/9uXnrpJZM/f37j6upqHn/8cTNo0CCbOjt27DDh4eHG3d3d5M2b1zz11FNm06ZNWYpn4sSJJjAw0Li4uJjq1aub9evXp2qPxmT+8+H69eumR48extvb2+TLl8+8+OKL5tixY5laMswYY44cOWKaNGli8ubNawoVKmR69uxpvvvuu1Rt5s8//zRhYWHG3d3dFCpUyHTs2NG6RNztn4OJiYmme/fuxsfHx1gsFpu2n9nPq6wYM2aMcXd3T7UcWe/evU2pUqWMi4uL8fHxMa1bt7ZZ7u123333nalfv77NZ/vkyZNT1StRokSaSzru3bvXSDJ9+vTJMN7du3cbZ2dns3PnzlTbpk+fbkqWLGm8vb1Nnz59bJacM8aYkJAQ89prr2V4DuBhYzEmh3/+BYActGvXLlWpUkVfffVVpobE4eFy8OBBBQcHa8WKFdYemIeRn5+f2rRpow8++CCnQ3lo9OrVS+vXr9f27dsz7OmePn262rVrp61bt2Z60j7g3yIuLk6lSpXSqFGjbJYwfNTs2rVLVatW1Y4dO2zuUwdyA+7pBvCvcfu6pCnGjh0rBwcHm0mXkHuUKlVKHTp00IgRI3I6lHT98ccfun79ut5+++2cDuWhceHCBX322WcaPnx4rp/UDshpXl5e6t+/vz744IN7Wo0itxgxYoRefvllEm7kSvR0A/jXGDZsmLZv366nnnpKefLk0YoVK7RixQrrveoAHk70dAMAcjMmUgPwr1G7dm2tXLlS7777rq5cuaLixYtr6NChqZYyAwAAALILPd0AAAAAANhJrrin+5NPPlHJkiXl6uqqkJAQ/fLLLzkdEgAAAAAAGXrok+45c+aoT58+GjJkiHbs2KHKlSsrPDxcZ8+ezenQAAAAAAC4q4d+eHlISIhq1KihCRMmSJKSk5NVrFgxde/eXQMGDMhw/+TkZJ08eVIeHh7MkAoAAAAAyBbGGF2+fFmFCxeWg0P6/dkP9URqN2/e1Pbt2zVw4EBrmYODg8LCwrR58+Y090lISFBCQoL1+YkTJ1SuXDm7xwoAAAAA+Pc5duyYihYtmu72h3p4+fnz55WUlCQ/Pz+bcj8/P50+fTrNfaKjo+Xl5WV9kHADAAAAAOzFw8Pjrtsf6qT7XgwcOFBxcXHWx7Fjx3I6JAAAAADAIyqj25gf6uHlhQoVkqOjo86cOWNTfubMGfn7+6e5j4uLi1xcXB5EeAAAAAAA3NVD3dPt7OysatWqafXq1day5ORkrV69WqGhoTkYGQAAAAAAGXuoe7olqU+fPmrbtq2qV6+umjVrauzYsbp69aratWuX06EBAAAAAHBXD33S3aJFC507d06DBw/W6dOn9cQTT+i7775LNbkaAAAAAAAPm4d+ne77FR8fLy8vr5wOAwAAAADwCIqLi5Onp2e62x/qe7oBAAAAAMjNSLoBAAAAALATkm4AAAAAAOyEpBsAAAAAADsh6QYAAAAAwE5IugEAAAAAsBOSbgAAAAAA7ISkGwAAAAAAOyHpBgAAAADATki6AQAAAACwE5JuAAAAAADshKQbAAAAAAA7IekGAAAAAMBOSLoBAAAAALATkm4AAAAAAOyEpBsAAAAAADsh6QYAAAAAwE5IugEAAAAAsBOSbgAAAAAA7ISkGwAAAAAAOyHpBgAAAADATki6AQAAAACwE5JuAAAAAADshKQbAAAAAAA7IekGAAAAAMBOSLoBAAAAALATkm4AAAAAAOyEpBsAAAAAADsh6QYAAAAAwE5IugEAAAAAsJMcTbqjo6NVo0YNeXh4yNfXV02bNlVsbKxNnRs3bigqKkre3t5yd3dXRESEzpw5k0MRAwAAAACQeTmadK9bt05RUVH6+eeftXLlSt26dUuNGzfW1atXrXV69+6tJUuW6Ntvv9W6det08uRJNWvWLAejBgAAAAAgcyzGGJPTQaQ4d+6cfH19tW7dOtWrV09xcXHy8fHRrFmz9PLLL0uS9u7dq7Jly2rz5s2qVatWhseMj4+Xl5eXvUMHAAAAAPwLxcXFydPTM93tD9U93XFxcZKkggULSpK2b9+uW7duKSwszFonODhYxYsX1+bNm9M8RkJCguLj420eAAAAAADkhIcm6U5OTlavXr1Up04dVahQQZJ0+vRpOTs7K3/+/DZ1/fz8dPr06TSPEx0dLS8vL+ujWLFi9g4dAAAAAIA05cnpAFJERUXp999/14YNG+7rOAMHDlSfPn2sz+Pj41WsWLEMu/wBAADw4FgslpwOAQAeiIci6e7WrZuWLl2q9evXq2jRotZyf39/3bx5U5cuXbLp7T5z5oz8/f3TPJaLi4tcXFzsHTIAAAAAABnK0aTbGKPu3btrwYIFWrt2rQIDA222V6tWTU5OTlq9erUiIiIkSbGxsTp69KhCQ0OzdC4mUwMAAAAAPGg5mnRHRUVp1qxZWrRokTw8PKz3aXt5ecnNzU1eXl7q0KGD+vTpo4IFC8rT01Pdu3dXaGhopmYuBwAAAAAgJ+XokmHp3cszbdo0RUZGSpJu3Lihvn37avbs2UpISFB4eLgmTpyY7vDyO7FkGAAAAADAXjKaP+yhWqfbHki6AQAAAAD2kqvW6QYAAAAA4FFC0g0AAAAAgJ2QdAMAAAAAYCck3QAAAAAA2AlJNwAAAAAAdkLSDQAAAACAnZB0AwAAAABgJyTdAAAAAADYSbYm3deuXcvOwwEAAAAAkKtlOelu1KiRTpw4kar8l19+0RNPPJEdMQEAAAAA8EjIctLt6uqqSpUqac6cOZKk5ORkDR06VHXr1tVzzz2X7QECAAAAAJBb5cnqDsuWLdMnn3yi9u3ba9GiRTp8+LCOHDmipUuXqnHjxvaIEQAAAACAXCnLSbckRUVF6fjx4xo5cqTy5MmjtWvXqnbt2tkdGwAAAAAAuVqWh5dfvHhRERERmjRpkqZMmaLmzZurcePGmjhxoj3iAwAAAAAg17IYY0xWdihSpIgCAwM1c+ZMBQYGSpLmzJmjrl27qlatWlq2bJldAr1X8fHx8vLyyukwAAAAAACPoLi4OHl6eqa7Pcs93V26dNH69eutCbcktWjRQr/++qtu3rx5b1ECAAAAAPAIynJP9+1u3LghV1fX7Iwn29HTDQAAAACwl2zv6U5OTta7776rIkWKyN3dXQcPHpQkDRo0SJ9//vm9RwoAAAAAwCMmy0n38OHDNX36dI0aNUrOzs7W8goVKuizzz7L1uAAAAAAAMjNspx0f/nll5o6dapeffVVOTo6WssrV66svXv3ZmtwAAAAAADkZllOuk+cOKHSpUunKk9OTtatW7eyJSgAAAAAAB4FWU66y5Urp59++ilV+dy5c1WlSpVsCQoAAAAAgEdBnqzuMHjwYLVt21YnTpxQcnKy5s+fr9jYWH355ZdaunSpPWIEAAAAACBXynJP93/+8x8tWbJEq1atUr58+TR48GDt2bNHS5Ys0dNPP22PGAEAAAAAyJXua53u3IB1ugEAAAAA9pLt63QDAAAAAIDMydQ93QUKFJDFYsnUAf/+++/7CggAAAAAgEdFppLusWPHWv994cIFDR8+XOHh4QoNDZUkbd68Wd9//70GDRpklyABAAAAAMiNsnxPd0REhJ566il169bNpnzChAlatWqVFi5cmJ3x3Tfu6QYAAAAA2EtG93RnOel2d3fXrl27VLp0aZvy/fv364knntCVK1fuLVI7IekGAAAAANhLtk+k5u3trUWLFqUqX7Rokby9vbN6OKsRI0bIYrGoV69e1rIbN24oKipK3t7ecnd3V0REhM6cOXPP5wAAAAAA4EHK1D3dtxs2bJjeeOMNrV27ViEhIZKkLVu26LvvvtOnn356T0Fs3bpVU6ZMUaVKlWzKe/furWXLlunbb7+Vl5eXunXrpmbNmmnjxo33dB4AAAAAAB6kLPd0R0ZGauPGjfL09NT8+fM1f/58eXp6asOGDYqMjMxyAFeuXNGrr76qTz/9VAUKFLCWx8XF6fPPP9eYMWPUsGFDVatWTdOmTdOmTZv0888/Z/k8AAAAAAA8aFnu6ZakkJAQxcTEZEsAUVFRev755xUWFqbhw4dby7dv365bt24pLCzMWhYcHKzixYtr8+bNqlWrVprHS0hIUEJCgvV5fHx8tsQJAAAAAEBW3VPSnZycrP379+vs2bNKTk622VavXr1MH+frr7/Wjh07tHXr1lTbTp8+LWdnZ+XPn9+m3M/PT6dPn073mNHR0Ro2bFimYwAAAAAAwF6ynHT//PPPat26tY4cOaI7Jz63WCxKSkrK1HGOHTumnj17auXKlXJ1dc1qGOkaOHCg+vTpY30eHx+vYsWKZdvxAQAAAADIrCwn3V26dFH16tW1bNkyBQQEyGKx3NOJt2/frrNnz6pq1arWsqSkJK1fv14TJkzQ999/r5s3b+rSpUs2vd1nzpyRv79/usd1cXGRi4vLPcUEAAAAAEB2ynLSvW/fPs2dOzfVOt1Z1ahRI/322282Ze3atVNwcLDefvttFStWTE5OTlq9erUiIiIkSbGxsTp69KhCQ0Pv69wAAAAAADwIWU66Q0JCtH///vtOuj08PFShQgWbsnz58snb29ta3qFDB/Xp00cFCxaUp6enunfvrtDQ0HQnUQMAAAAA4GGS5aS7e/fu6tu3r06fPq2KFSvKycnJZvuda23fj48++kgODg6KiIhQQkKCwsPDNXHixGw7PgAAAAAA9mQxd86GlgEHh9RLe1ssFhljsjSR2oMSHx8vLy+vnA4DAAAAAPAIiouLk6enZ7rbs9zTfejQofsKCAAAAACAf4ssJ90lSpSwRxwAAAAAADxyMpV0L168WM8++6ycnJy0ePHiu9Zt0qRJtgQGAAAAAEBul6l7uh0cHHT69Gn5+vqmeU+39WDc0w0AAAAA+BfJlnu6k5OT0/w3AAAAAABIX/rd1gAAAAAA4L6QdAMAAAAAYCck3QAAAAAA2AlJNwAAAAAAdkLSDQAAAACAnWRq9vI7JScna//+/Tp79myq2czr1auXLYEBAAAAAJDbZTnp/vnnn9W6dWsdOXJEdy7x/TCu0w0AAAAAQE7JctLdpUsXVa9eXcuWLVNAQIAsFos94gIAAAAAINezmDu7qzOQL18+/frrrypdurS9YspW8fHx8vLyyukwAAAAAACPoLi4OHl6eqa7PcsTqYWEhGj//v33FRQAAAAAAP8GWR5e3r17d/Xt21enT59WxYoV5eTkZLO9UqVK2RYcAAAAAAC5WZaHlzs4pO4ct1gsMsY8lBOpMbwcAAAAAGAvGQ0vz3JP96FDh+4rIAAAAAAA/i2ynHSXKFHCHnEAAAAAAPDIyXLSLUkHDhzQ2LFjtWfPHklSuXLl1LNnTwUFBWVrcAAAAAAA5GZZnr38+++/V7ly5fTLL7+oUqVKqlSpkrZs2aLy5ctr5cqV9ogRAAAAAIBcKcsTqVWpUkXh4eEaMWKETfmAAQP0ww8/aMeOHdka4P1iIjUAAAAAgL1kNJFalpNuV1dX/fbbbypTpoxN+V9//aVKlSrpxo0b9xapnZB0AwAAAADsJaOkO8vDy318fLRr165U5bt27ZKvr29WDwcAAAAAwCMryxOpdezYUZ06ddLBgwdVu3ZtSdLGjRs1cuRI9enTJ9sDBAAAAAAgt8ry8HJjjMaOHavRo0fr5MmTkqTChQvrrbfeUo8ePWSxWOwS6L1ieDkAAAAAwF6y9Z7uxMREzZo1S+Hh4fLz89Ply5clSR4eHvcfqZ2QdAMAAAAA7CXbJ1LLmzev9uzZoxIlStx3cA8CSTcAAAAAwF6yfSK1mjVraufOnfcVFAAAAAAA/wZZTrq7du2qvn37asKECdq8ebN2795t88iqEydO6LXXXpO3t7fc3NxUsWJFbdu2zbrdGKPBgwcrICBAbm5uCgsL0759+7J8HgAAAAAAHrQsDy93cEidp1ssFhljZLFYlJSUlOljXbx4UVWqVNFTTz2lN998Uz4+Ptq3b5+CgoIUFBQkSRo5cqSio6M1Y8YMBQYGatCgQfrtt9/0559/ytXVNcNzMLwcAAAAAGAv2X5P95EjR+66PSv3eg8YMEAbN27UTz/9lOZ2Y4wKFy6svn37ql+/fpL+eUF+fn6aPn26WrZsmeE5SLoBAAAAAPaS7Ul3dipXrpzCw8N1/PhxrVu3TkWKFFHXrl3VsWNHSdLBgwcVFBSknTt36oknnrDuV79+fT3xxBP6+OOPMzwHSTcAAAAAwF4ySrrzZPWAX3755V23t2nTJtPHOnjwoCZNmqQ+ffrov//9r7Zu3aoePXrI2dlZbdu21enTpyVJfn5+Nvv5+flZt90pISFBCQkJ1ufx8fGZjgcAAAAAgOyU5aS7Z8+eNs9v3bqla9euydnZWXnz5s1S0p2cnKzq1avr/ffflyRVqVJFv//+uyZPnqy2bdtmNTRJUnR0tIYNG3ZP+wIAAAAAkJ2yPHv5xYsXbR5XrlxRbGys6tatq9mzZ2fpWAEBASpXrpxNWdmyZXX06FFJkr+/vyTpzJkzNnXOnDlj3XangQMHKi4uzvo4duxYlmICAAAAACC7ZDnpTkuZMmU0YsSIVL3gGalTp45iY2Ntyv766y/rZGyBgYHy9/fX6tWrrdvj4+O1ZcsWhYaGpnlMFxcXeXp62jwAAAAAAMgJWR5enu6B8uTRyZMns7RP7969Vbt2bb3//vtq3ry5fvnlF02dOlVTp06V9M9SZL169dLw4cNVpkwZ65JhhQsXVtOmTbMrdAAAAAAA7CLLSffixYttnhtjdOrUKU2YMEF16tTJ0rFq1KihBQsWaODAgXrnnXcUGBiosWPH6tVXX7XW6d+/v65evapOnTrp0qVLqlu3rr777rtMrdENAAAAAEBOyvKSYQ4OtiPSLRaLfHx81LBhQ40ePVoBAQHZGuD9YskwAAAAAIC9ZPuSYcnJyfcVEAAAAAAA/xb3PJHazZs3FRsbq8TExOyMBwAAAACAR0aWk+5r166pffv2yps3r8qXL29d3qt79+4aMWJEtgcIAAAAAEBuleWke+DAgdq9e7fWrl1rM5lZWFiY5syZk63BAQAAAACQm2X5nu6FCxdqzpw5qlWrliwWi7W8fPnyOnDgQLYGBwAAAABAbpblnu5z587J19c3VfnVq1dtknAAAAAAAP7tspx0V69eXcuWLbM+T0m0P/vsM4WGhmZfZAAAAAAA5HJZHl7+/vvv69lnn9Wff/6pxMREffzxx/rzzz+1adMmrVu3zh4xAgAAAACQK2W5p7tu3bratWuXEhMTVbFiRf3www/y9fXV5s2bVa1aNXvECAAAAABArmQxxpicDsKe4uPj5eXlldNhAAAAAAAeQXFxcfL09Ex3e5Z7ugEAAAAAQOZk+p5uBweHDGcnt1gsSkxMvO+gAAAAAAB4FGQ66V6wYEG62zZv3qxx48YpOTk5W4ICAAAAAOBRkOmk+z//+U+qstjYWA0YMEBLlizRq6++qnfeeSdbgwMAAAAAIDe7p3u6T548qY4dO6pixYpKTEzUrl27NGPGDJUoUSK74wMAAAAAINfKUtIdFxent99+W6VLl9Yff/yh1atXa8mSJapQoYK94gMAAAAAINfK9PDyUaNGaeTIkfL399fs2bPTHG4OAAAAAAD+v0yv0+3g4CA3NzeFhYXJ0dEx3Xrz58/PtuCyA+t0AwAAAADsJaN1ujPd092mTZsMlwwDAAAAAAD/X6Z7unMreroBAAAAAPaSbT3duV1GbwQAAAAeHEZQAvi3uKclwwAAAAAAQMb+NT3dDDEHAAAAADxo9HQDAAAAAGAnJN0AAAAAANgJSTcAAAAAAHZC0g0AAAAAgJ2QdAMAAAAAYCck3QAAAAAA2AlJNwAAAAAAdpKjSXdSUpIGDRqkwMBAubm5KSgoSO+++66MMdY6xhgNHjxYAQEBcnNzU1hYmPbt25eDUQMAAAAAkDk5mnSPHDlSkyZN0oQJE7Rnzx6NHDlSo0aN0vjx4611Ro0apXHjxmny5MnasmWL8uXLp/DwcN24cSMHIwcAAAAAIGMWc3u38gP2wgsvyM/PT59//rm1LCIiQm5ubvrqq69kjFHhwoXVt29f9evXT5IUFxcnPz8/TZ8+XS1btszwHPHx8fLy8rLbawAAAAAA/HvFxcXJ09Mz3e052tNdu3ZtrV69Wn/99Zck6ddff9WGDRv07LPPSpIOHTqk06dPKywszLqPl5eXQkJCtHnz5hyJGQAAAACAzMqTkycfMGCA4uPjFRwcLEdHRyUlJem9997Tq6++Kkk6ffq0JMnPz89mPz8/P+u2OyUkJCghIcH6PD4+3k7RAwAAAABwdzna0/3NN98oJiZGs2bN0o4dOzRjxgx9+OGHmjFjxj0fMzo6Wl5eXtZHsWLFsjFiAAAAAAAyL0eT7rfeeksDBgxQy5YtVbFiRb3++uvq3bu3oqOjJUn+/v6SpDNnztjsd+bMGeu2Ow0cOFBxcXHWx7Fjx+z7IgAAAAAASEeOJt3Xrl2Tg4NtCI6OjkpOTpYkBQYGyt/fX6tXr7Zuj4+P15YtWxQaGprmMV1cXOTp6WnzAAAAAAAgJ+ToPd0vvvii3nvvPRUvXlzly5fXzp07NWbMGLVv316SZLFY1KtXLw0fPlxlypRRYGCgBg0apMKFC6tp06Y5GToAAAAAABnK0SXDLl++rEGDBmnBggU6e/asChcurFatWmnw4MFydnaWJBljNGTIEE2dOlWXLl1S3bp1NXHiRD322GOZOgdLhgEAAAAA7CWjJcNyNOl+EEi6AQAAAAD28lCv0w0AAAAAwKOMpBsAAAAAADsh6QYAAAAAwE5IugEAAAAAsBOSbgAAAAAA7ISkGwAAAAAAOyHpBgAAAADATki6AQAAAACwE5JuAAAAAADshKQbAAAAAAA7IekGAAAAAMBOSLoBAAAAALATkm4AAAAAAOyEpBsAAAAAADsh6QYAAAAAwE5IugEAAAAAsBOSbgAAAAAA7ISkGwAAAAAAOyHpBgAAAADATki6AQAAAACwE5JuAAAAAADshKQbAAAAAAA7IekGAAAAAMBOSLoBAAAAALATkm4AAAAAAOyEpBsAAAAAADsh6QYAAAAAwE5IugEAAAAAsBOSbgAAAAAA7ISkGwAAAAAAOyHpBgAAAADATki6AQAAAACwE5JuAAAAAADs5JFPuo0xOR0CAAAAAOARlVHO+cgn3ZcvX87pEAAAAAAAj6iMck6LecS7gpOTk3Xy5El5eHjIYrFkad/4+HgVK1ZMx44dk6enp50ixL8d7QwPAu0MDwLtDA8C7QwPAu0MmWGM0eXLl1W4cGE5OKTfn53nAcaUIxwcHFS0aNH7Ooanpyf/2WB3tDM8CLQzPAi0MzwItDM8CLQzZMTLyyvDOo/88HIAAAAAAHIKSTcAAAAAAHZC0n0XLi4uGjJkiFxcXHI6FDzCaGd4EGhneBBoZ3gQaGd4EGhnyE6P/ERqAAAAAADkFHq6AQAAAACwE5JuAAAAAADshKQbAAAAAAA7Iem+i08++UQlS5aUq6urQkJC9Msvv+R0SHiEDB06VBaLxeYRHByc02Ehl1u/fr1efPFFFS5cWBaLRQsXLrTZbozR4MGDFRAQIDc3N4WFhWnfvn05EyxyrYzaWWRkZKrr2zPPPJMzwSJXio6OVo0aNeTh4SFfX181bdpUsbGxNnVu3LihqKgoeXt7y93dXRERETpz5kwORYzcKDPtrEGDBqmuZ126dMmhiJFbkXSnY86cOerTp4+GDBmiHTt2qHLlygoPD9fZs2dzOjQ8QsqXL69Tp05ZHxs2bMjpkJDLXb16VZUrV9Ynn3yS5vZRo0Zp3Lhxmjx5srZs2aJ8+fIpPDxcN27ceMCRIjfLqJ1J0jPPPGNzfZs9e/YDjBC53bp16xQVFaWff/5ZK1eu1K1bt9S4cWNdvXrVWqd3795asmSJvv32W61bt04nT55Us2bNcjBq5DaZaWeS1LFjR5vr2ahRo3IoYuRWzF6ejpCQENWoUUMTJkyQJCUnJ6tYsWLq3r27BgwYkMPR4VEwdOhQLVy4ULt27crpUPCIslgsWrBggZo2bSrpn17uwoULq2/fvurXr58kKS4uTn5+fpo+fbpatmyZg9Eit7qznUn/9HRfunQpVQ84cK/OnTsnX19frVu3TvXq1VNcXJx8fHw0a9Ysvfzyy5KkvXv3qmzZstq8ebNq1aqVwxEjN7qznUn/9HQ/8cQTGjt2bM4Gh1yNnu403Lx5U9u3b1dYWJi1zMHBQWFhYdq8eXMORoZHzb59+1S4cGGVKlVKr776qo4ePZrTIeERdujQIZ0+fdrm2ubl5aWQkBCubch2a9eula+vrx5//HG9+eabunDhQk6HhFwsLi5OklSwYEFJ0vbt23Xr1i2b61lwcLCKFy/O9Qz37M52liImJkaFChVShQoVNHDgQF27di0nwkMulienA3gYnT9/XklJSfLz87Mp9/Pz0969e3MoKjxqQkJCNH36dD3++OM6deqUhg0bpieffFK///67PDw8cjo8PIJOnz4tSWle21K2AdnhmWeeUbNmzRQYGKgDBw7ov//9r5599llt3rxZjo6OOR0ecpnk5GT16tVLderUUYUKFST9cz1zdnZW/vz5bepyPcO9SqudSVLr1q1VokQJFS5cWLt379bbb7+t2NhYzZ8/PwejRW5D0g3kkGeffdb670qVKikkJEQlSpTQN998ow4dOuRgZABwf26/VaFixYqqVKmSgoKCtHbtWjVq1CgHI0NuFBUVpd9//515T2BX6bWzTp06Wf9dsWJFBQQEqFGjRjpw4ICCgoIedJjIpRhenoZChQrJ0dEx1QyYZ86ckb+/fw5FhUdd/vz59dhjj2n//v05HQoeUSnXL65teNBKlSqlQoUKcX1DlnXr1k1Lly7Vjz/+qKJFi1rL/f39dfPmTV26dMmmPtcz3Iv02llaQkJCJInrGbKEpDsNzs7OqlatmlavXm0tS05O1urVqxUaGpqDkeFRduXKFR04cEABAQE5HQoeUYGBgfL397e5tsXHx2vLli1c22BXx48f14ULF7i+IdOMMerWrZsWLFigNWvWKDAw0GZ7tWrV5OTkZHM9i42N1dGjR7meIdMyamdpSZkAl+sZsoLh5eno06eP2rZtq+rVq6tmzZoaO3asrl69qnbt2uV0aHhE9OvXTy+++KJKlCihkydPasiQIXJ0dFSrVq1yOjTkYleuXLH59f3QoUPatWuXChYsqOLFi6tXr14aPny4ypQpo8DAQA0aNEiFCxe2mXkayMjd2lnBggU1bNgwRUREyN/fXwcOHFD//v1VunRphYeH52DUyE2ioqI0a9YsLVq0SB4eHtb7tL28vOTm5iYvLy916NBBffr0UcGCBeXp6anu3bsrNDSUmcuRaRm1swMHDmjWrFl67rnn5O3trd27d6t3796qV6+eKlWqlMPRI1cxSNf48eNN8eLFjbOzs6lZs6b5+eefczokPEJatGhhAgICjLOzsylSpIhp0aKF2b9/f06HhVzuxx9/NJJSPdq2bWuMMSY5OdkMGjTI+Pn5GRcXF9OoUSMTGxubs0Ej17lbO7t27Zpp3Lix8fHxMU5OTqZEiRKmY8eO5vTp0zkdNnKRtNqXJDNt2jRrnevXr5uuXbuaAgUKmLx585qXXnrJnDp1KueCRq6TUTs7evSoqVevnilYsKBxcXExpUuXNm+99ZaJi4vL2cCR67BONwAAAAAAdsI93QAAAAAA2AlJNwAAAAAAdkLSDQAAAACAnZB0AwAAAABgJyTdAAAAAADYCUk3AAAAAAB2QtINAAAAAICdkHQDAAAAAGAnJN0AAOSgoUOH6oknnrD7eaZPn678+fPb7fhr166VxWLRpUuX7us4kZGRatq0abbEBADAw4CkGwCAbHDu3Dm9+eabKl68uFxcXOTv76/w8HBt3LjRWsdisWjhwoU2+/Xr10+rV69+wNFmv9q1a+vUqVPy8vLK6VAAAHio5MnpAAAAeBRERETo5s2bmjFjhkqVKqUzZ85o9erVunDhwl33c3d3l7u7+wOK0n6cnZ3l7++f02EAAPDQoacbAID7dOnSJf30008aOXKknnrqKZUoUUI1a9bUwIED1aRJE0lSyZIlJUkvvfSSLBaL9fmdw8tThle///778vPzU/78+fXOO+8oMTFRb731lgoWLKiiRYtq2rRp1n3SGtq9a9cuWSwWHT58OM2Y0xrG3atXLzVo0MD6fO7cuapYsaLc3Nzk7e2tsLAwXb16Nc3j3RlDynD277//XmXLlpW7u7ueeeYZnTp1yrpPUlKS+vTpo/z588vb21v9+/eXMcbmuMnJyYqOjlZgYKDc3NxUuXJlzZ07V5JkjFFYWJjCw8Ot+/39998qWrSoBg8enGacAAA8aCTdAADcp5Te6oULFyohISHNOlu3bpUkTZs2TadOnbI+T8uaNWt08uRJrV+/XmPGjNGQIUP0wgsvqECBAtqyZYu6dOmizp076/jx43Z5PZJ06tQptWrVSu3bt9eePXu0du1aNWvWLFVSfDfXrl3Thx9+qJkzZ2r9+vU6evSo+vXrZ90+evRoTZ8+XV988YU2bNigv//+WwsWLLA5RnR0tL788ktNnjxZf/zxh3r37q3XXntN69atk8Vi0YwZM7R161aNGzdOktSlSxcVKVKEpBsA8NBgeDkAAPcpT548mj59ujp27KjJkyeratWqql+/vlq2bKlKlSpJknx8fCRJ+fPnz3AYdsGCBTVu3Dg5ODjo8ccf16hRo3Tt2jX997//lSQNHDhQI0aM0IYNG9SyZUu7vKZTp04pMTFRzZo1U4kSJSRJFStWzNIxbt26pcmTJysoKEiS1K1bN73zzjvW7WPHjtXAgQPVrFkzSdLkyZP1/fffW7cnJCTo/fff16pVqxQaGipJKlWqlDZs2KApU6aofv36KlKkiKZMmaI2bdro9OnTWr58uXbu3Kk8efiKAwB4ONDTDQBANoiIiNDJkye1ePFiPfPMM1q7dq2qVq2q6dOnZ/lY5cuXl4PD//+I9vPzs0l4HR0d5e3trbNnz2ZH6GmqXLmyGjVqpIoVK+qVV17Rp59+qosXL2bpGHnz5rUm3JIUEBBgjTkuLk6nTp1SSEiIdXuePHlUvXp16/P9+/fr2rVrevrpp62jCdzd3fXll1/qwIED1nqvvPKKXnrpJY0YMUIffvihypQpc68vGwCAbEfSDQBANnF1ddXTTz+tQYMGadOmTYqMjNSQIUOyfBwnJyeb5xaLJc2y5ORkSbIm6LcP/b5169Zdz+Hg4JBqqPjt+zg6OmrlypVasWKFypUrp/Hjx+vxxx/XoUOH7ut1ZGV4+pUrVyRJy5Yt065du6yPP//803pft/TPMPbt27fL0dFR+/bty/TxAQB4EEi6AQCwk3LlytlMPObk5KSkpKRsP0/K0PXbJynbtWtXhvvcXj+tfSwWi+rUqaNhw4Zp586dcnZ2TnXP9b3y8vJSQECAtmzZYi1LTEzU9u3brc/LlSsnFxcXHT16VKVLl7Z5FCtWzFqvb9++cnBw0IoVKzRu3DitWbMmW2IEACA7cMMTAAD36cKFC3rllVfUvn17VapUSR4eHtq2bZtGjRql//znP9Z6JUuW1OrVq1WnTh25uLioQIEC2XL+lCR06NCheu+99/TXX39p9OjRd92nYcOG+uCDD/Tll18qNDRUX331lX7//XdVqVJFkrRlyxatXr1ajRs3lq+vr7Zs2aJz586pbNmy2RKzJPXs2VMjRoxQmTJlFBwcrDFjxtjMwO7h4aF+/fqpd+/eSk5OVt26dRUXF6eNGzfK09NTbdu21bJly/TFF19o8+bNqlq1qt566y21bdtWu3fvzrb3FwCA+0FPNwAA98nd3V0hISH66KOPVK9ePVWoUEGDBg1Sx44dNWHCBGu90aNHa+XKlSpWrJg1uc0OTk5Omj17tvbu3atKlSpp5MiRGj58+F33CQ8P16BBg9S/f3/VqFFDly9fVps2bazbPT09tX79ej333HN67LHH9L///U+jR4/Ws88+m21x9+3bV6+//rratm2r0NBQeXh46KWXXrKp8+6772rQoEGKjo5W2bJl9cwzz2jZsmUKDAzUuXPn1KFDBw0dOlRVq1aVJA0bNkx+fn7q0qVLtsUJAMD9sJis3FwFAAAAAAAyjZ5uAAAAAADshKQbAAAAAAA7IekGAAAAAMBOSLoBAAAAALATkm4AAAAAAOyEpBsAAAAAADsh6QYAAAAAwE5IugEAAAAAsBOSbgAAAAAA7ISkGwAAAAAAOyHpBgAAAADATki6AQAAAACwk/8HxegUGdG5sfQAAAAASUVORK5CYII=", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(10, 3))\n", "ax.imshow(aa1.nrn_masks.T.numpy(), aspect=\"auto\", cmap=\"Greys\", interpolation=\"nearest\")\n", "ax.set_xlabel(\"Stimulus index\")\n", "ax.set_ylabel(\"Neuron index\")\n", "ax.set_title(f\"AA1 coverage — black = (stim, neuron) pair has recorded data \"\n", " f\"({100 * aa1.nrn_masks.float().mean().item():.1f}%)\")\n", "plt.tight_layout()\n", "plt.show()\n" ] }, { "cell_type": "markdown", "id": "c4b34606", "metadata": {}, "source": [ "## 6. Selecting a sub-population\n", "\n", "`__getitem__` and `__len__` operate on the subset of neurons currently\n", "selected by `self.I`. Three helpers populate it:\n", "\n", "- `select_neuron(i)` — single neuron by integer index.\n", "- `select_population([i, j, …])` — an explicit list of indices.\n", "- `select_pop_by_nrn_attr(attr, value)` — all neurons whose\n", " `nrn_meta[attr] == value`. Dict-based metadata makes this\n", " idiomatic: e.g. `select_pop_by_nrn_attr(\"area\", \"MLd\")`.\n", "\n", "Selection is stateful — call as many times as you like; the dataset reflects\n", "the most recent call on every subsequent `__getitem__`.\n" ] }, { "cell_type": "code", "execution_count": 7, "id": "c332120e", "metadata": { "execution": { "iopub.execute_input": "2026-04-25T10:47:03.237234Z", "iopub.status.busy": "2026-04-25T10:47:03.236977Z", "iopub.status.idle": "2026-04-25T10:47:03.307340Z", "shell.execute_reply": "2026-04-25T10:47:03.305876Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Selected 50 MLd neurons out of 100 total.\n", "len(aa1) now returns: 30 (stims with >=1 valid selected neuron)\n" ] } ], "source": [ "aa1.select_pop_by_nrn_attr(\"area\", \"MLd\")\n", "\n", "print(f\"Selected {len(aa1.I)} MLd neurons out of {aa1.N_neurons} total.\")\n", "print(f\"len(aa1) now returns: {len(aa1)} (stims with >=1 valid selected neuron)\")\n" ] }, { "cell_type": "markdown", "id": "136797dc", "metadata": {}, "source": [ "\n", "## 6.1 What `len(ds)` and `ds[i]` actually expose\n", "\n", "A subtle but important detail: both `len(ds)` and `ds[i]` are **filtered\n", "by the current neuron selection**. They expose only the stimuli for which\n", "at least one currently selected neuron has valid response data. Stimuli\n", "that the selection has no data on are hidden — `len(ds)` does not count\n", "them, and `ds[i]` never returns them.\n", "\n", "This is what makes a `DataLoader(ds, ...)` safe under any selection:\n", "iterating `range(len(ds))` is guaranteed to visit only stimuli with real\n", "response data for the selected neurons, never a fully-NaN slab.\n", "\n", "The stored attributes (`ds.stims`, `ds.responses`, `ds.stim_meta`,\n", "`ds.nrn_masks`, …) are *not* filtered — they keep the dataset's full\n", "structure regardless of `self.I`. Use them for direct access to a\n", "specific raw stim. The filter applies only at the iteration interface.\n" ] }, { "cell_type": "code", "execution_count": 8, "id": "bbb57f8c", "metadata": { "execution": { "iopub.execute_input": "2026-04-25T10:47:03.310676Z", "iopub.status.busy": "2026-04-25T10:47:03.310320Z", "iopub.status.idle": "2026-04-25T10:47:03.640224Z", "shell.execute_reply": "2026-04-25T10:47:03.639009Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "selected: gg0304_10_B\n", " this neuron has data for 30 / 30 stims\n", " len(aa1) = 30 # exactly the iterable subset\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ " aa1[0] stim_meta = {'name': '058767E725C83836F405A97FD7D1E751.wav', 'type': 'conspecific'} # first iterable stim\n", " aa1[len(aa1)] -> IndexError (no fully-NaN slab returned)\n", " aa1.stims[0] is still raw stim 0 (conspecific); raw access bypasses the filter.\n" ] } ], "source": [ "\n", "# concrete demo of the filter: pick one neuron with sparse coverage and\n", "# observe how len(ds) and the iterable space adapt.\n", "aa1.select_neuron(neuron_idx)\n", "print(f\"selected: {aa1.nrn_meta[neuron_idx]['cell_id']}\")\n", "print(f\" this neuron has data for {int(aa1.nrn_masks[:, neuron_idx].sum())} / {aa1.get_S()} stims\")\n", "print(f\" len(aa1) = {len(aa1)} # exactly the iterable subset\")\n", "print(f\" aa1[0] stim_meta = {aa1[0][3]} # first iterable stim\")\n", "try:\n", " aa1[len(aa1)]\n", "except IndexError as e:\n", " print(f\" aa1[len(aa1)] -> IndexError (no fully-NaN slab returned)\")\n", "print(f\" aa1.stims[0] is still raw stim 0 ({aa1.stim_meta[0]['type']}); \"\n", " f\"raw access bypasses the filter.\")\n" ] }, { "cell_type": "markdown", "id": "e892f354", "metadata": {}, "source": [ "## 7. Batching with a DataLoader\n", "\n", "Because stim duration `T_s` and repeat count `R_{s,n}` both vary across items,\n", "the default PyTorch collate cannot stack items into a single tensor. Use\n", "`deepSTRF.utils.data.neural_collate`, which right-pads stims with zeros and\n", "responses with NaN, then derives a `valid_mask` via `~responses.isnan()`.\n", "\n", "One yielded batch is a 4-tuple: `(stims, responses, valid_mask, stim_metas)`.\n", "See `data_paradigm.md` §5 for exact shapes and §6 for the recommended loss\n", "pattern (`pred_psth[valid]` boolean indexing).\n" ] }, { "cell_type": "code", "execution_count": 9, "id": "f3c28972", "metadata": { "execution": { "iopub.execute_input": "2026-04-25T10:47:03.642718Z", "iopub.status.busy": "2026-04-25T10:47:03.642256Z", "iopub.status.idle": "2026-04-25T10:47:04.135101Z", "shell.execute_reply": "2026-04-25T10:47:04.133978Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "stims shape : (4, 1, 32, 460) (B, 1, F, T_max)\n", "responses shape : (4, 1, 10, 460) (B, N_selected, R_max, T_max)\n", "valid_mask shape : (4, 1, 10, 460) (B, N_selected, R_max, T_max) bool\n", "stim_metas : [{'name': '058767E725C83836F405A97FD7D1E751.wav', 'type': 'conspecific'}, {'name': '0A07B255BF830083B6726388CA8510BA.wav', 'type': 'conspecific'}, {'name': '1470489635DD93410408CE9F8FB2F7D9.wav', 'type': 'conspecific'}, {'name': '42FED9F3EF45A238202B050B06F91652.wav', 'type': 'conspecific'}]\n", "\n", "valid fraction across the batch: 0.878\n", "per-item count of fully-NaN slabs (neuron×stim pairs without data): [0, 0, 0, 0]\n" ] } ], "source": [ "loader = DataLoader(aa1, batch_size=4, shuffle=False, collate_fn=neural_collate)\n", "batch = next(iter(loader))\nstims, responses, valid_mask, stim_metas = batch['stims'], batch['responses'], batch['valid_mask'], batch['stim_meta']\n", "\n", "print(f\"stims shape : {tuple(stims.shape)} (B, 1, F, T_max)\")\n", "print(f\"responses shape : {tuple(responses.shape)} (B, N_selected, R_max, T_max)\")\n", "print(f\"valid_mask shape : {tuple(valid_mask.shape)} (B, N_selected, R_max, T_max) bool\")\n", "print(f\"stim_metas : {stim_metas}\")\n", "print()\n", "print(f\"valid fraction across the batch: {valid_mask.float().mean().item():.3f}\")\n", "print(f\"per-item count of fully-NaN slabs (neuron×stim pairs without data): \"\n", " f\"{[int((~valid_mask[b].any(dim=(1, 2))).sum()) for b in range(valid_mask.shape[0])]}\")\n" ] }, { "cell_type": "markdown", "id": "6bdf98f8", "metadata": {}, "source": [ "## 8. Switching to AA2\n", "\n", "AA2 uses the exact same interface — just a different data directory and a\n", "richer set of recording areas and stimulus classes. Skipping the smoothing\n", "below to speed up instantiation.\n" ] }, { "cell_type": "code", "execution_count": null, "id": "0bf714dd", "metadata": { "execution": { "iopub.execute_input": "2026-04-25T10:47:04.137506Z", "iopub.status.busy": "2026-04-25T10:47:04.137179Z", "iopub.status.idle": "2026-04-25T10:47:41.494819Z", "shell.execute_reply": "2026-04-25T10:47:41.494035Z" } }, "outputs": [], "source": "aa2 = CRCNSAA2Dataset(\n download=True,\n areas=(\"Field_L\", \"mld\", \"OV\", \"CM\"),\n stimuli=(\"conspecific\", \"songrip\", \"flatrip\"),\n dt_ms=DT_MS,\n smooth=False,\n)\nprint(aa2)\nprint(f\"coverage: {int(aa2.nrn_masks.sum())} / {aa2.nrn_masks.numel()} \"\n f\"({100 * aa2.nrn_masks.float().mean().item():.1f}%)\")\nprint(f\"one nrn_meta entry: {aa2.nrn_meta[0]}\")\n\n# same API, same dict from the collate:\naa2.select_population(list(range(min(aa2.N_neurons, 32)))) # take 32 neurons to keep the batch small\nloader = DataLoader(aa2, batch_size=4, shuffle=False, collate_fn=neural_collate)\nbatch = next(iter(loader))\nstims, responses, valid_mask, stim_metas = batch['stims'], batch['responses'], batch['valid_mask'], batch['stim_meta']\nprint(f\"AA2 batch stims shape : {tuple(stims.shape)}\")\nprint(f\"AA2 batch responses shape : {tuple(responses.shape)}\")\nprint(f\"AA2 batch valid_mask shape : {tuple(valid_mask.shape)}\")\n" }, { "cell_type": "markdown", "id": "1b4e63c0", "metadata": {}, "source": [ "## Recap\n", "\n", "- Every deepSTRF dataset exposes the same core attributes — `stims`,\n", " `responses`, `stim_meta`, `nrn_meta` — plus the derived\n", " `nrn_masks` property, regardless of modality or source.\n", "- Missingness on the response side is encoded as NaN (see `data_paradigm.md`\n", " §4 for why). The `nrn_masks` property is the canonical \"does this\n", " (stim, neuron) pair have data\" query — computed on the fly from responses.\n", "- `neural_collate` handles the ragged batch-padding and emits a\n", " `(B, N, R, T)` `valid_mask` alongside the NaN-padded responses.\n", "- Neuron sub-population selection is stateful via `self.I` — the same\n", " dataset object works as a single-neuron or a population dataset depending\n", " on the most recent `select_*` call.\n", "\n", "Next: see the `fit_audio_*.ipynb` notebooks for examples of actually fitting\n", "a model on these datasets.\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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 }