#packmode normal #modloaded deepmoblearning import mods.gregtech.recipe.RecipeMap; import crafttweaker.data.IData; import crafttweaker.world.IFacing; import crafttweaker.item.IItemStack; import crafttweaker.item.IItemCondition; import scripts.common.makeShaped as makeShaped; // from DML's config val mobs as int[string] = { // mob RF/t "zombie": 64, "skeleton": 64, "creeper": 64, "spider": 64, "slime": 64, "witch": 512, "blaze": 1024, "ghast": 1024, "wither_skeleton": 1024, "enderman": 2048, "wither": 6666, "dragon": 6666, "shulker": 512, "guardian": 1024, "thermal_elemental": 1024 }; val pristine_types as IItemStack[string] = { // mob pristine type "zombie": , "skeleton": , "creeper": , "spider": , "slime": , "witch": , "blaze": , "ghast": , "wither_skeleton": , "enderman": , "wither": , "dragon": , "shulker": , "guardian": , "thermal_elemental": }; val model_prefix = "deepmoblearning:data_model_"; val pristine_prefix = "deepmoblearning:pristine_matter_"; //// from DML's config //val pristine_chances as int[] = [ // 5, // 10, // 20, // 30 //]; // //// from DML's config //val maxExperience as int[] = [ // 0, // 50, // 250, // 500 //]; //Recipe for Controller // Moved to Groovy val DATA_MODEL_MAXIMUM_TIER = 4; val PRISTINE_CHANCE_FIXED = 30; // in % for mob, cost in mobs { dme_sim_chamber.recipeBuilder() .duration(301) .EUt(cost / 4 as int) .inputs() .notConsumable(itemUtils.getItem(model_prefix + mob).withEmptyTag()) .outputs(pristine_types[mob]) .chancedOutput(itemUtils.getItem(pristine_prefix + mob), PRISTINE_CHANCE_FIXED * 100, 0) .buildAndRegister(); }