20230119 noon
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parent
2da034fa38
commit
1e92b3d2d0
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@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -235,6 +235,9 @@
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"#删除\\quad\n",
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"data = re.sub(r\"\\\\q+uad\",\"\",data)\n",
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"\n",
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"#删除~\n",
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"data = re.sub(r\"~\",\"\",data)\n",
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"\n",
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"\n",
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"\n",
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"data1 = data #替换后暂存data1\n",
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@ -287,7 +290,8 @@
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" equation1 = re.sub(r\"([0-9A-Z])\\s+([0-9A-Z])\",lambda x:x.group(1)+x.group(2),equation1)\n",
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" #改变组合数和排列数\n",
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" equation1 = re.sub(r\"([CP])(_[^_\\^]{,5}\\^)\",lambda x:r\"\\mathrm{\"+x.group(1)+\"}\"+x.group(2),equation1)\n",
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" \n",
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" #改单位\n",
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" equation1 = re.sub(r\"mathrm\\{cm\\}\",\"text{cm}\",equation1)\n",
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" modified_equations.append(equation1)\n",
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"\n",
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"\n",
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@ -315,8 +319,10 @@
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" modified_data = re.sub(r\" \\$\",\"$\",modified_data)\n",
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"#mathpix的错别字修改\n",
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"modified_data = modified_data.replace(\"雉\",\"锥\")\n",
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"modified_data = modified_data.replace(\"粗圆\",\"椭圆\")\n",
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"modified_data = re.sub(\"[粗秿]圆\",\"椭圆\",modified_data)\n",
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"modified_data = modified_data.replace(\"针角\",\"钝角\")\n",
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"modified_data = re.sub(\"投郑\",\"投掷\",modified_data)\n",
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"modified_data = re.sub(\"抛郑\",\"抛掷\",modified_data)\n",
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"#mathpix的自由向量修改\n",
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"modified_data = modified_data.replace(r\"\\vec\",r\"\\overrightarrow \")\n",
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"modified_data = modified_data.replace(r\"\\bar\",r\"\\overline \")\n",
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@ -341,6 +347,9 @@
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"modified_data = re.sub(r\"\\\\{\\\\begin\\{array\\}\\{[rcl]*\\}\",r\"\\\\begin{cases}\",modified_data)\n",
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"modified_data = re.sub(r\"\\\\end{array}\",r\"\\\\end{cases}\",modified_data)\n",
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"\n",
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"#冒号后加空格\n",
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"modified_data = re.sub(r\":([\\S])\", lambda x:\": \"+x.group(1),modified_data)\n",
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"\n",
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"#识别填空题加空格\n",
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"modified_data = re.sub(r\"([\\u4e00-\\u9fa5\\$])[\\s]*\\n\\\\item\",lambda x: x.group(1)+\"\\\\blank{50}.\\n\\\\item\",modified_data)\n",
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"\n",
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@ -378,12 +387,12 @@
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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": "3.9.15"
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"version": "3.8.15"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "ff3c292c316ba85de6f1ad75f19c731e79d694e741b6f515ec18f14996fe48dc"
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"hash": "42dd566da87765ddbe9b5c5b483063747fec4aacc5469ad554706e4b742e67b2"
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}
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}
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},
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