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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# 分析结果\n", | ||
| "\n", | ||
| "这是一个用于分析模型率定后测试结果的 Jupyter Notebook。读取各个exp下面的结果文件看看。" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 9, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "Please Check your directory:\n", | ||
| "ROOT_DIR of the repo: d:\\code\\hydro-model-xaj\n", | ||
| "DATASET_DIR of the repo: d:\\data\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import os\n", | ||
| "import sys\n", | ||
| "from pathlib import Path\n", | ||
| "\n", | ||
| "sys.path.append(os.path.dirname(Path(os.path.abspath('')).parent))\n", | ||
| "import definitions" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 10, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import pandas as pd\n", | ||
| "import matplotlib.pyplot as plt" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 14, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "metric_mean_file = Path(os.path.join(\"D:/研究生/毕业论文/new毕业论文/预答辩/碧流河水库/模型运行/basins_test_metrics_mean_all_cases.csv\"))\n", | ||
| "metric_median_file = Path(os.path.join(\"D:/研究生/毕业论文/new毕业论文/预答辩/碧流河水库/模型运行/basins_test_metrics_median_all_cases.csv\"))" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 15, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "metric_mean = pd.read_csv(metric_mean_file, index_col=0)\n", | ||
| "metric_median = pd.read_csv(metric_median_file, index_col=0)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 16, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/html": [ | ||
| "<div>\n", | ||
| "<style scoped>\n", | ||
| " .dataframe tbody tr th:only-of-type {\n", | ||
| " vertical-align: middle;\n", | ||
| " }\n", | ||
| "\n", | ||
| " .dataframe tbody tr th {\n", | ||
| " vertical-align: top;\n", | ||
| " }\n", | ||
| "\n", | ||
| " .dataframe thead th {\n", | ||
| " text-align: right;\n", | ||
| " }\n", | ||
| "</style>\n", | ||
| "<table border=\"1\" class=\"dataframe\">\n", | ||
| " <thead>\n", | ||
| " <tr style=\"text-align: right;\">\n", | ||
| " <th></th>\n", | ||
| " <th>Bias</th>\n", | ||
| " <th>RMSE</th>\n", | ||
| " <th>ubRMSE</th>\n", | ||
| " <th>Corr</th>\n", | ||
| " <th>R2</th>\n", | ||
| " <th>NSE</th>\n", | ||
| " <th>KGE</th>\n", | ||
| " <th>FHV</th>\n", | ||
| " <th>FLV</th>\n", | ||
| " </tr>\n", | ||
| " </thead>\n", | ||
| " <tbody>\n", | ||
| " <tr>\n", | ||
| " <th>HFsources</th>\n", | ||
| " <td>-10.431724</td>\n", | ||
| " <td>84.941974</td>\n", | ||
| " <td>84.29898</td>\n", | ||
| " <td>0.625164</td>\n", | ||
| " <td>0.380791</td>\n", | ||
| " <td>0.380791</td>\n", | ||
| " <td>0.308037</td>\n", | ||
| " <td>-30.076788</td>\n", | ||
| " <td>-100.0</td>\n", | ||
| " </tr>\n", | ||
| " </tbody>\n", | ||
| "</table>\n", | ||
| "</div>" | ||
| ], | ||
| "text/plain": [ | ||
| " Bias RMSE ubRMSE Corr R2 NSE \\\n", | ||
| "HFsources -10.431724 84.941974 84.29898 0.625164 0.380791 0.380791 \n", | ||
| "\n", | ||
| " KGE FHV FLV \n", | ||
| "HFsources 0.308037 -30.076788 -100.0 " | ||
| ] | ||
| }, | ||
| "execution_count": 16, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "metric_mean" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 17, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/html": [ | ||
| "<div>\n", | ||
| "<style scoped>\n", | ||
| " .dataframe tbody tr th:only-of-type {\n", | ||
| " vertical-align: middle;\n", | ||
| " }\n", | ||
| "\n", | ||
| " .dataframe tbody tr th {\n", | ||
| " vertical-align: top;\n", | ||
| " }\n", | ||
| "\n", | ||
| " .dataframe thead th {\n", | ||
| " text-align: right;\n", | ||
| " }\n", | ||
| "</style>\n", | ||
| "<table border=\"1\" class=\"dataframe\">\n", | ||
| " <thead>\n", | ||
| " <tr style=\"text-align: right;\">\n", | ||
| " <th></th>\n", | ||
| " <th>Bias</th>\n", | ||
| " <th>RMSE</th>\n", | ||
| " <th>ubRMSE</th>\n", | ||
| " <th>Corr</th>\n", | ||
| " <th>R2</th>\n", | ||
| " <th>NSE</th>\n", | ||
| " <th>KGE</th>\n", | ||
| " <th>FHV</th>\n", | ||
| " <th>FLV</th>\n", | ||
| " </tr>\n", | ||
| " </thead>\n", | ||
| " <tbody>\n", | ||
| " <tr>\n", | ||
| " <th>HFsources</th>\n", | ||
| " <td>-10.431724</td>\n", | ||
| " <td>84.941974</td>\n", | ||
| " <td>84.29898</td>\n", | ||
| " <td>0.625164</td>\n", | ||
| " <td>0.380791</td>\n", | ||
| " <td>0.380791</td>\n", | ||
| " <td>0.308037</td>\n", | ||
| " <td>-30.076788</td>\n", | ||
| " <td>-100.0</td>\n", | ||
| " </tr>\n", | ||
| " </tbody>\n", | ||
| "</table>\n", | ||
| "</div>" | ||
| ], | ||
| "text/plain": [ | ||
| " Bias RMSE ubRMSE Corr R2 NSE \\\n", | ||
| "HFsources -10.431724 84.941974 84.29898 0.625164 0.380791 0.380791 \n", | ||
| "\n", | ||
| " KGE FHV FLV \n", | ||
| "HFsources 0.308037 -30.076788 -100.0 " | ||
| ] | ||
| }, | ||
| "execution_count": 17, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "metric_median" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3.9.7 ('xaj')", | ||
| "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": "3.10.12" | ||
| }, | ||
| "orig_nbformat": 4, | ||
| "vscode": { | ||
| "interpreter": { | ||
| "hash": "5ff2b0240d3185dc85fb5f0a6365eefe977ea7c2afca8c64838dc9fcf4f02a96" | ||
| } | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |
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