diff --git a/fsrs4anki_optimizer.ipynb b/fsrs4anki_optimizer.ipynb index b763f92..6edbe2d 100644 --- a/fsrs4anki_optimizer.ipynb +++ b/fsrs4anki_optimizer.ipynb @@ -5,9 +5,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# FSRS4Anki v4.4.7 Optimizer\n", + "# FSRS4Anki v4.5.0 Optimizer\n", "\n", - "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/v4.4.7/fsrs4anki_optimizer.ipynb)\n", + "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/v4.5.0/fsrs4anki_optimizer.ipynb)\n", "\n", "↑ Click the above button to open the optimizer on Google Colab.\n", "\n", @@ -63,7 +63,11 @@ "revlog_start_date = \"2006-10-05\" #YYYY-MM-DD\n", "\n", "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n", - "filter_out_suspended_cards = False" + "filter_out_suspended_cards = False\n", + "\n", + "# Red: 1, Orange: 2, Green: 3, Blue: 4, Pink: 5, Turquoise: 6, Purple: 7\n", + "# Set it to [1, 2] if you don't want the optimizer to use the review logs from cards with red or orange flag.\n", + "filter_out_flags = []" ] }, { @@ -108,14 +112,14 @@ } ], "source": [ - "%pip install -q FSRS-Optimizer==4.6.0\n", + "%pip install -q FSRS-Optimizer==4.7.0\n", "# for local development\n", "# import os\n", "# import sys\n", "# sys.path.insert(0, os.path.abspath('../fsrs-optimizer/src/fsrs_optimizer/'))\n", "import fsrs_optimizer as optimizer\n", "optimizer = optimizer.Optimizer()\n", - "optimizer.anki_extract(filename, filter_out_suspended_cards)" + "optimizer.anki_extract(filename, filter_out_suspended_cards, filter_out_flags)" ] }, { @@ -155,7 +159,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2b9a7397bae24e2e9d4bc7aae072b085", + "model_id": "0bd6eb35225a4848b5f6df5fffe628e7", "version_major": 2, "version_minor": 0 }, @@ -177,7 +181,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d399cbfef5ad4e48851cc12fa13a99b9", + "model_id": "6261d3d6980545d18f13abea475efe4f", "version_major": 2, "version_minor": 0 }, @@ -198,7 +202,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "85f099284cf9463d80629818e6781d07", + "model_id": "12ce6fb307474237ba61c1abe52b2035", "version_major": 2, "version_minor": 0 }, @@ -295,7 +299,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f3bc8e53bb144f919df35fa49c81bd5c", + "model_id": "68e2ff66905b4623b4a872211edfd4dc", "version_major": 2, "version_minor": 0 }, @@ -318,7 +322,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b2a5fe39b405495ab95af604b436c9ee", + "model_id": "ab156adb8f8b403b9228af4b7297858b", "version_major": 2, "version_minor": 0 }, @@ -340,7 +344,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "884fadc6889443568aa33bddd9121a41", + "model_id": "e29459db4c3447e38f3e798794483abe", "version_major": 2, "version_minor": 0 }, @@ -362,7 +366,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "abcbc4a32d2d489e9c696af1b0135c6d", + "model_id": "978110966459443a88529aed99d6da56", "version_major": 2, "version_minor": 0 }, @@ -384,7 +388,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c37040e0b5e341fd89f075278d58d3f2", + "model_id": "a9d374391e954d50a0b91e667534b35f", "version_major": 2, "version_minor": 0 }, @@ -406,7 +410,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "085b253661074d4db1ccff93b5e8c252", + "model_id": "632709669bab4d5281893c2f83b51105", "version_major": 2, "version_minor": 0 }, @@ -659,7 +663,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "eb0e33463aef4f50a2a8ad6ac2854028", + "model_id": "7b3dd85f06bc4fd5834d8b54b2cb7ca3", "version_major": 2, "version_minor": 0 }, @@ -862,179 +866,179 @@ "data": { "text/html": [ "\n", - "
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