添加规划计算器实用程序, 并添加 shebang 和一些优化

estimator.py

@@ -0,0 +1,62 @@
+#!/usr/bin/env python3
+# 模拟规划完成所有记忆单元集文件的最小时间
+import os
+import particles as pt
+import datetime
+import pathlib
+import math
+
+MINIMAL_REPEATATION = 2
+FILTER = "ALL"
+WORST_EF = 5
+PAYLOAD = 8
+
+print("SM-2 任务预规划实用程序")
+print(f"运行时刻: {datetime.datetime.now()}")
+print(f" > 筛选器模式: {FILTER}")
+print(f" > 最小重复次数设置: {MINIMAL_REPEATATION}")
+print(f" > 最坏难度系数: {WORST_EF}")
+print(f" > 单日单元负荷: {PAYLOAD}")
+
+print("--------")
+
+filelist = []
+
+if FILTER == "ALL":
+    for i in os.listdir('./nucleon'):
+        if "toml" in i:
+            print("扫描到记忆单元集: " + i)
+            filelist.append(i)
+    print(f"共需记忆 {len(filelist)} 个记忆单元集")
+else:
+    filelist = [FILTER]
+
+print("--------")
+time_counter = 0
+text_counter = 0
+content_counter = 0
+for i in filelist:
+    print(f"处理: {i}")
+    nucu = pt.NucleonUnion(pathlib.Path("./nucleon/" + i))
+    print(f"记忆单元数: {len(nucu.nucleons)}")
+    content_cnt = 0
+    metadata_trsl_cnt = 0
+    metadata_note_cnt = 0
+    metadata_kwrd_cnt = 0
+    for i in nucu.nucleons:
+        content_cnt += len(i.content)
+        metadata_trsl_cnt += len(str(i.metadata["translation"]))
+        metadata_kwrd_cnt += len(str(i.metadata["keyword_note"]))
+        metadata_note_cnt += len(str(i.metadata["note"]))
+    print(" - 原文文字数: " + str(content_cnt))
+    metadata_cnt = metadata_kwrd_cnt + metadata_note_cnt + metadata_trsl_cnt
+    print(" - 元数据字数: " + str(metadata_cnt) + f"\n = {metadata_trsl_cnt}[翻译] + {metadata_kwrd_cnt}[关键词] + {metadata_note_cnt}[笔记]")
+    print(f" - 总文字数: {content_cnt + metadata_cnt}")
+    print(f"独占记忆时间: {len(nucu.nucleons) / PAYLOAD} -> {math.ceil(len(nucu.nucleons) / PAYLOAD)}")
+    text_counter += (content_cnt + metadata_cnt)
+    content_counter += content_cnt
+    time_counter += math.ceil(len(nucu.nucleons) / PAYLOAD)
+    print("--------")
+for i in range(MINIMAL_REPEATATION):
+    print(f"若按计划进行, 最长需要 {time_counter + (i + 1) * 6} 天完成全部内容的第 {i + 1} 次记忆")
+print(f"规划包含 {content_counter} 字, 附加了 {text_counter - content_counter} 字的元数据内容, 共计 {text_counter} 字")