language fallback, ai ordering, screenshots, contributors
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@@ -9,6 +9,7 @@ Matthew Allred ("Kameone") for design of the v1.1 UI and providing MacOS install
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"nimets123" for the German translation and sound effects.
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"nowoowoo" for a fix to the parser for SGF files with extra line breaks.
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Sergio Villegas ("serpiente") for the Spanish translation.
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"divanorama" and Alexander Kiselev for the Russian translation.
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Additional thanks to:
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"Seventeen" for explanatory youtube videos.
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@@ -1,11 +1,11 @@
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# <a name="manual"></a> KaTrain v1.1
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# <a name="manual"></a> KaTrain v1.2
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[](https://github.com/sanderland/katrain/releases)
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[](https://en.wikipedia.org/wiki/MIT_License)
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[](https://pepy.tech/project/katrain)
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[](https://liberapay.com/sanderbaduk/)
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[](https://liberapay.com/sanderbaduk/)
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[](https://discord.com/channels/417022162348802048/629446365688365067)
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KaTrain is a tool for analyzing and playing go with AI feedback from KataGo.
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@@ -57,12 +57,12 @@ This section describes the available AIs, with strength based on their current O
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* Recommended options for serious play include:
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* **[9p+]** **KataGo** is full KataGo, above professional level. The analysis and feedback given is always based on this full strength KataGo AI.
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* **[15k - 3d]** **Calibrated Rank Bot** was calibrated on various bots (e.g. GnuGo and Pachi at different strength settings) to play a balanced game from the opening to the endgame without making serious (DDK) blunders. Further discussion can be found on [this](https://github.com/sanderland/katrain/issues/44) thread.
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* **[~3k]** **ScoreLoss** is KataGo analyzing as usual, but
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choosing from potential moves depending on the expected score loss, leading to a varied style with mostly small mistakes.
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* **[~4d]** **Policy** uses the top move from the policy network (it's 'shape sense' without reading).
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* **[~5k]** **Policy Weighted** picks a random move weighted by the policy, leading to a varied style with mostly small mistakes, and occasional blunders due to a lack of reading.
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* **[~8k]** **Blinded Policy** picks a number of moves at random and play the best move among them, being effectively 'blind' to part of the board each turn.
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* **[15k - 3d]** **Calibrated Rank Bot** was calibrated on various bots (e.g. GnuGo and Pachi at different strength settings) to play a balanced game from the opening to the endgame without making serious (DDK) blunders. Further discussion can be found on [this](https://github.com/sanderland/katrain/issues/44) thread.
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* Options that are more on the 'fun and experimental' side include:
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* Variants of **Blinded Policy**, which use the same basic strategy, but with a twist.:
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* **[~5k]** **Local Style** will consider mostly moves close to the last move.
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@@ -132,8 +132,8 @@ In addition to shortcuts mentioned above and those shown in the main menu:
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## <a name="support"></a> Support / Contribute
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[](https://github.com/sanderland/katrain/issues)
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[](CONTRIBUTORS)
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[](https://liberapay.com/sanderbaduk/)
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[](CONTRIBUTORS)
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[](https://liberapay.com/sanderbaduk/)
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[](https://github.com/sponsors/sanderland)
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* Ideas, feedback, and contributions to code or translations are all very welcome.
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@@ -30,10 +30,10 @@ AI_STRATEGIES_POLICY = [AI_WEIGHTED, AI_POLICY] + AI_STRATEGIES_PICK
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AI_STRATEGIES = AI_STRATEGIES_ENGINE + AI_STRATEGIES_POLICY
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AI_STRATEGIES_RECOMMENDED_ORDER = [
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AI_DEFAULT,
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AI_RANK,
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AI_SCORELOSS,
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AI_POLICY,
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AI_WEIGHTED,
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AI_RANK,
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AI_PICK,
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AI_LOCAL,
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AI_TENUKI,
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@@ -56,7 +56,7 @@ class Lang(Observable):
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self.font_name = self.FONTS.get(lang) or DEFAULT_FONT
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i18n_dir, _ = os.path.split(find_package_resource("katrain/i18n/__init__.py"))
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locale_dir = os.path.join(i18n_dir, "locales")
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locales = gettext.translation("katrain", locale_dir, languages=[lang])
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locales = gettext.translation("katrain", locale_dir, languages=[lang,DEFAULT_LANGUAGE])
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self.ugettext = locales.gettext
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# update all the kv rules attached to this text
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