77 lines
1.4 MiB
Plaintext
77 lines
1.4 MiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "2968d030-90e6-4e13-afb9-da6916ab054b",
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"metadata": {},
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"outputs": [],
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"source": [
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"from tools import *"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "47040e2b-dc42-458c-900d-f82e02890332",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Clean Data Shape: (8000, 128)\n",
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"Noisy Data Shape: (8000, 128)\n"
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]
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 1500x1700 with 18 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"# 测试数据加载和噪声添加\n",
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"clean_data, noisy_data = get_kuramoto_sivashinsky()\n",
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"print(\"Clean Data Shape:\", clean_data.shape)\n",
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"print(\"Noisy Data Shape:\", noisy_data.shape)\n",
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"visualize_ks_denoising(clean_data, noisy_data, clean_data)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7c5f13bd-424b-436c-8cf7-20888bdbd9db",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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