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--- a +++ b/No1-boxplot.ipynb @@ -0,0 +1,4750 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import plotly.express as px\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "def boxplot(output_name, network, y_min=None, y_max=None):\n", + " df_dice = pd.read_csv(f\"outputs/{network}/{output_name}/infer_dice_class.csv\")\n", + " df_iou = pd.read_csv(f\"outputs/{network}/{output_name}/infer_iou_class.csv\")\n", + "\n", + " df_dice['type'] = 'dice'\n", + " df_iou['type'] = 'iou'\n", + "\n", + " df_combined = pd.concat([df_dice, df_iou])\n", + " df_combined.reset_index(drop=True, inplace=True)\n", + " df_final = pd.melt(df_combined, id_vars=['type'], var_name='classes', value_name='scores')\n", + " df_final.sort_values(['type', 'classes'], inplace=True)\n", + " df_final.reset_index(drop=True, inplace=True)\n", + "\n", + " fig = px.box(df_final, x=\"classes\", y=\"scores\", color=\"type\")\n", + " fig.update_traces(quartilemethod=\"exclusive\")\n", + " fig.update_layout(\n", + " width=1000, \n", + " height=500,\n", + " font=dict(\n", + " size=18 \n", + " )\n", + " )\n", + " if y_min is not None and y_max is not None:\n", + " fig.update_yaxes(range=[y_min, y_max])\n", + " fig.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### VHSCDD $(256 \\times 256)$" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "alignmentgroup": "True", + "hovertemplate": "type=dice<br>classes=%{x}<br>scores=%{y}<extra></extra>", + "legendgroup": "dice", + "marker": { + "color": "#636efa" + }, + "name": "dice", + "notched": false, + "offsetgroup": "dice", + "orientation": "v", + "quartilemethod": 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